167 Quantization Jobs

Senior Data Scientist (Deep Learning and Artificial Intelligence) Job Description We aim to bring about a new paradigm in medical image diagnostics; providing intelligent, holistic, ethical, explainable and patient centric care. We are looking for innovative problem solvers who love solving problems. We want people who can empathize with the consumer, understand business problems, and design and deliver intelligent products. People who are looking to extend artificial intelligence into unexplored areas. Your primary focus will be in applying deep learning and artificial intelligence techniques to the domain of medical image analysis. Responsibilities Selecting features, building and optimizing classifier engines using deep learning techniques. Understanding the problem and applying the suitable image processing techniques Use techniques from artificial intelligence/deep learning to solve supervised and unsupervised learning problems. Understanding and designing solutions for complex problems related to medical image analysis by using Deep Learning/Object Detection/Image Segmentation. Recommend and implement best practices around the application of statistical modeling. Create, train, test, and deploy various neural networks to solve complex problems. Develop and implement solutions to fit business problems which may include applying algorithms from a standard statistical tool, deep learning or custom algorithm development. Understanding the requirements and designing solutions and architecture in accordance with them is important. Participate in code reviews, sprint planning, and Agile ceremonies to drive high-quality deliverables. Design and implement scalable data science architectures for training, inference, and deployment pipelines. Ensure code quality, readability, and maintainability by enforcing software engineering best practices within the data science team. Optimize models for production, including quantization, pruning, and latency reduction for real-time inference. Drive the adoption of versioing strategies for models, datasets, and experiments (e.g., using MLFlow, DVC). Contribute to the architectural design of data platforms to support large-scale experimentation and production workloads. Skills and Qualifications Strong software engineering skills in Python (or other languages used in data science) with emphasis on clean code, modularity, and testability. Excellent understanding and hands-on of Deep Learning techniques such as ANN, CNN, RNN, LSTM, Transformers, VAEs etc. Must have experience with Tensorflow or PyTorch framework in building, training, testing, and deploying neural networks. Experience in solving problems in the domain of Computer Vision. Knowledge of data, data augmentation, data curation, and synthetic data generation. Ability to understand the complete problem and design the solutions that best fit all the constraints. Knowledge of the common data science and deep learning libraries and toolkits such as Keras, Pandas, Scikit-learn, Numpy, Scipy, OpenCV etc. Good applied statistical skills, such as distributions, statistical testing, regression, etc. Exposure to Agile/Scrum methodologies and collaborative development practices. Experience with the development of RESTful APIs. The knowledge of libraries like FastAPI and the ability to apply it to deep learning architectures is essential. Excellent analytical and problem-solving skills with a good attitude and keen to adapt to evolving technologies. Experience with medical image analysis will be an advantage. Experience designing and building ML architecture components (e.g., feature stores, model registries, inference servers). Solid understanding of software design patterns, microservices, and cloud-native architectures. Expertise in model optimization techniques (e.g., ONNX conversion, TensorRT, model distillation) Education : BE/B Tech MS/M Tech (will be a bonus) Experience : 3+ Years Job Type: Full-time Ability to commute/relocate: Gurugram, Haryana: Reliably commute or planning to relocate before starting work (Required) Application Question(s): Do you have experience leading teams in AI Development? Do you have experience creating software architecture for production environment in AI applications? Experience: Deep learning: 3 years (Required) Computer vision: 3 years (Required) PyTorch: 3 years (Required) Work Location: In person

Senior Data Scientist (Deep Learning and Artificial Intelligence) Job Description We aim to bring about a new paradigm in medical image diagnostics; providing intelligent, holistic, ethical, explainable and patient centric care. We are looking for innovative problem solvers who love solving problems. We want people who can empathize with the consumer, understand business problems, and design and deliver intelligent products. People who are looking to extend artificial intelligence into unexplored areas. Your primary focus will be in applying deep learning and artificial intelligence techniques to the domain of medical image analysis. Responsibilities Selecting features, building and optimizing classifier engines using deep learning techniques. Understanding the problem and applying the suitable image processing techniques Use techniques from artificial intelligence/deep learning to solve supervised and unsupervised learning problems. Understanding and designing solutions for complex problems related to medical image analysis by using Deep Learning/Object Detection/Image Segmentation. Recommend and implement best practices around the application of statistical modeling. Create, train, test, and deploy various neural networks to solve complex problems. Develop and implement solutions to fit business problems which may include applying algorithms from a standard statistical tool, deep learning or custom algorithm development. Understanding the requirements and designing solutions and architecture in accordance with them is important. Participate in code reviews, sprint planning, and Agile ceremonies to drive high-quality deliverables. Design and implement scalable data science architectures for training, inference, and deployment pipelines. Ensure code quality, readability, and maintainability by enforcing software engineering best practices within the data science team. Optimize models for production, including quantization, pruning, and latency reduction for real-time inference. Drive the adoption of versioing strategies for models, datasets, and experiments (e.g., using MLFlow, DVC). Contribute to the architectural design of data platforms to support large-scale experimentation and production workloads. Skills and Qualifications Strong software engineering skills in Python (or other languages used in data science) with emphasis on clean code, modularity, and testability. Excellent understanding and hands-on of Deep Learning techniques such as ANN, CNN, RNN, LSTM, Transformers, VAEs etc. Must have experience with Tensorflow or PyTorch framework in building, training, testing, and deploying neural networks. Experience in solving problems in the domain of Computer Vision. Knowledge of data, data augmentation, data curation, and synthetic data generation. Ability to understand the complete problem and design the solutions that best fit all the constraints. Knowledge of the common data science and deep learning libraries and toolkits such as Keras, Pandas, Scikit-learn, Numpy, Scipy, OpenCV etc. Good applied statistical skills, such as distributions, statistical testing, regression, etc. Exposure to Agile/Scrum methodologies and collaborative development practices. Experience with the development of RESTful APIs. The knowledge of libraries like FastAPI and the ability to apply it to deep learning architectures is essential. Excellent analytical and problem-solving skills with a good attitude and keen to adapt to evolving technologies. Experience with medical image analysis will be an advantage. Experience designing and building ML architecture components (e.g., feature stores, model registries, inference servers). Solid understanding of software design patterns, microservices, and cloud-native architectures. Expertise in model optimization techniques (e.g., ONNX conversion, TensorRT, model distillation) Education : BE/B Tech MS/M Tech (will be a bonus) Experience : 3+ Years Job Type: Full-time Ability to commute/relocate: Gurugram, Haryana: Reliably commute or planning to relocate before starting work (Required) Application Question(s): Do you have experience leading teams in AI Development? Do you have experience creating software architecture for production environment in AI applications? Experience: Deep learning: 3 years (Required) Computer vision: 3 years (Required) PyTorch: 3 years (Required) Work Location: In person

Roles and Responsibilities: As a, Data scientist / Senior Data scientist you will solve some of the most impactful business problems for our clients using a variety of AI and ML technologies. You will collaborate with business partners and domain experts to design and develop innovative solutions on the data to achieve predefined outcomes. Engage with clients to understand current and future business goals and translate business problems into analytical frameworks Develop custom models based on in-depth understanding of underlying data, data structures, and business problems to ensure deliverables meet client needs Create repeatable, interpretable and scalable models Effectively communicate the analytics approach and insights to a larger business audience Collaborate with team members, peers and leadership at Tredence and client companies Qualification: Bachelor's or Master's degree in a quantitative field (CS, machine learning, mathematics, statistics) or equivalent experience. 3+ years of experience in data science, building hands-on ML models Experience with LMs (Llama (1/2/3), T5, Falcon, Langchain or framework similar like Langchain) Candidate must be aware of entire evolution history of NLP (Traditional Language Models to Modern Large Language Models), training data creation, training set-up and finetuning Candidate must be comfortable interpreting research papers and architecture diagrams of Language Models Candidate must be comfortable with LORA, RAG, Instruct fine-tuning, Quantization, etc. Experience leading the end-to-end design, development, and deployment of predictive modeling solutions. Excellent programming skills in Python. Strong working knowledge of Python’s numerical, data analysis, or AI frameworks such as NumPy, Pandas, Scikit-learn, Jupyter, etc. Advanced SQL skills with SQL Server and Spark experience. Knowledge of predictive/prescriptive analytics including Machine Learning algorithms (Supervised and Unsupervised) and deep learning algorithms and Artificial Neural Networks Experience with Natural Language Processing (NLTK) and text analytics for information extraction, parsing and topic modeling. Excellent verbal and written communication. Strong troubleshooting and problem-solving skills. Thrive in a fast-paced, innovative environment Experience with data visualization tools — PowerBI, Tableau, R Shiny, etc. preferred Experience with cloud platforms such as Azure, AWS is preferred but not require

About the Role: We are seeking an experienced MLOps Engineer to lead the deployment, scaling, and performance optimization of open-source Generative AI models on cloud infrastructure. You’ll work at the intersection of machine learning, DevOps, and cloud engineering to help productize and operationalize large-scale LLM and diffusion models. Key Responsibilities: Design and implement scalable deployment pipelines for open-source Gen AI models (LLMs, diffusion models, etc.). Fine-tune and optimize models using techniques like LoRA, quantization, distillation, etc. Manage inference workloads, latency optimization, and GPU utilization. Build CI/CD pipelines for model training, validation, and deployment. Integrate observability, logging, and alerting for model and infrastructure monitoring. Automate resource provisioning using Terraform, Helm, or similar tools on GCP/AWS/Azure. Ensure model versioning, reproducibility, and rollback using tools like MLflow, DVC, or Weights & Biases. Collaborate with data scientists, backend engineers, and DevOps teams to ensure smooth production rollouts. Required Skills & Qualifications: 5+ years of total experience in software engineering or cloud infrastructure. 3+ years in MLOps with direct experience in deploying large Gen AI models. Hands-on experience with open-source models (e.g., LLaMA, Mistral, Stable Diffusion, Falcon, etc.). Strong knowledge of Docker, Kubernetes, and cloud compute orchestration. Proficiency in Python and familiarity with model-serving frameworks (e.g., FastAPI, Triton Inference Server, Hugging Face Accelerate, vLLM). Experience with cloud platforms (GCP preferred, AWS or Azure acceptable). Familiarity with distributed training, checkpointing, and model parallelism. Good to Have: Experience with low-latency inference systems and token streaming architectures. Familiarity with cost optimization and scaling strategies for GPU-based workloads. Exposure to LLMOps tools (LangChain, BentoML, Ray Serve, etc.). Why Join Us: Opportunity to work on cutting-edge Gen AI applications across industries. Collaborative team with deep expertise in AI, cloud, and enterprise software. Flexible work environment with a focus on innovation and impact.

📢 We're Hiring: AI/ML Experts in Generative AI, LLMs & RAG At Botminds AI, we’re redefining end-to-end document automation with Generative AI, LLMs, and Retrieval-Augmented Generation (RAG). We’re looking for seasoned AI/ML professionals who are passionate about turning cutting-edge research into real-world impact. 🚀 What You’ll Do Build LLM-powered solutions for document understanding, summarization, and QA Architect RAG pipelines using vector DBs and embedding models Fine-tune open-source LLMs (LLaMA, Mistral, Falcon, etc.) Lead POCs with OpenAI, Claude, Gemini, etc. and benchmark results Collaborate with engineering/product teams to ship ML features Work with OCR outputs, unstructured data, and knowledge bases Stay updated on GenAI, LLM, and retrieval trends 🧠 What You Bring 10+ years of experience in ML, AI, and NLP | 2+ years specializing in LLMs and Generative AI Strong skills in Python, PyTorch/TensorFlow, Hugging Face, LangChain Experience with vector DBs (FAISS, Pinecone, Qdrant, Weaviate) Proven RAG pipeline development and prompt engineering LLM fine-tuning, quantization, scalable deployment expertise Bonus: OCR tools experience (Azure Form Recognizer, Tesseract, Google Vision) Solid understanding of MLOps and scalable ML systems 🌟 Why Join Botminds? Be on the frontlines of GenAI-powered enterprise automation Work in a lean, elite team that ships high-impact features fast Flat hierarchy, high ownership, innovation-first culture Shape the future of intelligent document processing 📩 Interested or know someone who fits? Reach out to Srividhya@botmonds.ai to apply now — let’s build the future of automation together!

We are looking for a Senior Data Scientist/TL in our EO Applied Data Science (EO Data) Team. Our mission is realized through foundational research and development in applied machine learning. With a plethora of Geospatial Data Science use-cases that we have solved so far, such as Land Use and Land Cover (LULC), Crop Classification, Sowing and Harvest Progression, Change Detection, Route Optimization, Satellite Image Time-Series (SITS) classification, Image2Image (I2I) Translation, Cross Modal Fusion etc, we are now focusing on advancing the next-generation Machine Learning (ML) applications, and surpass the State-Of-The-Art (SOTA), especially in more ambiguous, complex geographies. We look forward to applying our research to critical products, while touching the lives of millions of users, via revolutionary, real, and near-real time large-scale software systems utilizing Terabytes of data. At the core of such systems, we are envisioning foundational geospatial data science models that are season, modality and ground agnostic. We have been at the forefront of adaptable and efficient models, as evidenced by our findings through publications at top ML/GRS conferences. About SatSure: SatSure is a deep tech, decision intelligence company that leverages Earth-Observation (EO) data to solve crucial problems at the nexus of agriculture, finance, infrastructure, utilities, aviation, energy, climate, to name a few. Our goal is to create an impact for the other millions, focusing on the developing world. We want to make insights from earth observation data accessible to all. With a founding team having roots in the Indian Institute of Space Science and Technology (IIST), Indian Space Research Organisation (ISRO), Indian Institute of Remote Sensing (IIRS), and the leadership team having diverse backgrounds (IBM, Samsung, Intel, USC, IITKGP, IITG, IITM), we value technical innovation and scale. If you are interested in working in an environment that focuses on the impact on society, driven by cutting-edge technology, and where you will have the freedom to work on innovative ideas and be creative with no hierarchies, SatSure is the place for you. Roles & Responsibilities: Own a couple of technical roadmaps and charters for assisting the science manager in terms of resource management. Technically mentor science staff and projects. Work in collaboration with product owners, applied data scientists, MLOps, geospatial experts, platform engineers to envision solutions to real-world, ambiguous business use-cases with low latency/ high throughput. Focus on identifying and solving customer problems with simple and elegant solutions, while working backwards from customer requirements. Quickly propose and validate hypotheses to direct the product roadmaps. Own time-bound, End-to-End (E2E) solutioning of large-scale ML applications, ranging from resource, requirements gathering, data collection, cleaning and annotation, model development, validation, deployment, monitoring, etc. Brainstorm, deep dive, implement, debug into fundamentals of the systems (e.g., architectures, losses, efficiency, serving etc), while writing clean, production level code, and conduct A/B as necessary. Define proper output Data Science metrics and calibrate them to the desired business metrics. Clearly communicate findings verbally and in writing to stakeholders of varied backgrounds. Have attention to detail. Engage and initiate collaborative efforts to meet ambitious (applied research and product/client delivery) goals. Innovate and advance State-Of-The-Art (SOTA) in-house solutions, and communicate findings as IPs (patents, papers), as deemed applicable by business. Mentor junior staff, interns as applicable. Assist Science managers in effective project, resource management, hiring, and timely deliverables (in an agile manner), via showcasing strong sense of ownership and accountability. Qualification: M.Tech, MS (Research), PhD in a technical field (e.g., CS, EE, EC, Remote Sensing, etc), preferably from leading academic/ industrial labs/institutes, corporates. Undergraduates/Dual-Degree with research experience as mentioned below may also be considered. Experience working in industry (2-6 years of experience), on projects from proof-of-concept to deployment and monitoring, while partnering with business stakeholders, product managers, engineers, and other data scientists to translate business needs into technical, deployed solutions. 1-2 years of industry experience as a technical leader, as evidenced by simultaneous, multiple project and/or people management/mentorship instances. Demonstration of functioning in a matrixed organization while aligning cross-functional stakeholders towards shared goals, and exhibiting excellent behavioral skills. Must-have: To be eligible for this role, we are looking for candidates with the following qualifications: A proven track record of relevant experience in computer vision, NLP, learning theory, optimization, ML+Systems, foundational models, etc. Technically familiar with some, or most of (as evidenced by problem solving skills in novel scenarios): Convolutional Neural Networks (CNNs), LSTMs/RNNs/GRUs, Transformers, UNet, YOLO, RCNN, Encoder-Decoder Architectures, Generative Models (GAN, VAE, Diffusion), Contrastive Learning, Self-Supervised Learning, Semi-Supervised Learning, Representation Learning, Image Super Resolution, Traditional Machine Learning (Classification, Regression, Clustering), Active Learning, Learning with Noisy Labels, Multimodal Learning, Synthetic Aperture Radar (SAR)/VV-VH bands, Normalized Difference Vegetation Index (NDVI), False Colour Composite (FCC), Dimensionality Reduction (PCA, UMAP, Isomap), Time-Series Modeling/ Forecasting, Model compression (Distillation, Pruning, Quantization), Automatic Mixed Precision training, Fourier Neural Operator (FNO), Climate+AI, Domain Adaptation, Domain Generalization, Anomaly Detection etc. Candidates with prior publications in (main tracks/ workshops of) ICLR, CVPR, ICCV, ECCV, NeurIPS, ICML, AAAI, IJCAI, ACL, EMNLP, TACL, NAACL, TMLR, IGARSS, InGARSS, IEEE Transactions, etc, would have an edge too (with preference to first-authored ones). Proficiency in at least one general programming language (preferably, Python), along with strong hands-on experience with ML frameworks (e.g. PyTorch) in terms of training large, optimized, scalable, ML models. Strong verbal and written communication skills. Experience with SQL, large scale distributed systems (e.g., Spark), MLOps will be handy. Benefits: Medical Health Cover for you and your family including unlimited online doctor consultations Access to mental health experts for you and your family Dedicated allowances for learning and skill development Comprehensive leave policy with casual leaves, paid leaves, marriage leaves, bereavement leaves Twice a year appraisal Interview Process: Intro call Assessment Presentation Interview rounds (ideally up to 3-4 rounds) Culture Round / HR round Link to SatSure blogs

We're not your average tech company! Rightcrowd is a global leader in keeping people safe and organizations secure. We build smart solutions that manage who's on-site, what access they have, and ensure everything is compliant. Think big names – Fortune 50 and ASX 10 companies rely on us to tackle their toughest security challenges. We're a passionate, global team with offices in places like Australia, the USA, Belgium, India, and the Philippines, and we're on a mission to make the world a safer place, one clever line of code at a time. What We Offer Competitive salary and benefits. A collaborative, respectful, and high-accountability team culture. Opportunities for growth within a global finance team. Flexibility in a remote-friendly and dynamic work environment. Key Responsibilities Required Qualifications & Skills: Agentic AI Development & Code Generation: Design, implement, and lead the development of an advanced agentic AI system that can interpret user stories and autonomously generate production-ready code Research and implement state-of-the-art techniques in LLM prompting, fine-tuning, and orchestration to achieve optimal code generation results Architect robust evaluation systems to test, validate, and improve AI-generated code Seamlessly integrate AI-generated code into existing CI/CD pipelines Collaborate with product and engineering teams to refine inputs and ensure alignment with development standards AI Recommendation Engine Architecture: Architect a high-performance, scalable recommendation engine for the RightCrowd SmartAccess platform Design and implement AI-driven feature extraction pipelines Develop hybrid recommendation algorithms leveraging both collaborative filtering and content- based approaches Engineer systems for real-time inference and continuous model improvement Ensure the architecture integrates seamlessly with existing product infrastructure Natural Language Reporting System Development: Lead the end-to-end development of an AI-powered reporting system that translates natural language queries to SQL Engineer robust NLP components to accurately understand and parse user requests Build a reliable translation layer between natural language and database queries Implement data retrieval, processing, and presentation mechanisms Design systems for generating insights and visualizations from retrieved data Ensure appropriate data security and access controls Technical Leadership & Innovation: Provide architectural guidance across AI initiatives within the organization Design scalable, maintainable AI systems with consideration for cloud infrastructure and MLOps best practices Stay at the forefront of advancements in LLMs, agentic AI, and code generation technologies Mentor junior engineers and foster a culture of AI innovation Collaborate effectively with cross-functional teams Master's or Ph.D. in Computer Science, AI, or related field (or equivalent practical experience) 5+ years of experience building production-level AI systems with significant focus on LLMs and generative AI Demonstrated expertise in Python and modern AI frameworks (PyTorch, TensorFlow, Hugging Face Transformers) Extensive experience with LLM orchestration frameworks (LangChain, LangGraph, or similar) Proven track record designing and implementing agentic AI systems Strong proficiency in prompt engineering, fine-tuning, and optimization of LLMs Expert-level SQL skills and experience with database systems Experience with cloud platforms (AWS, Azure, GCP) and their AI/ML services Solid understanding of software engineering principles and best practices Experience with MLOps and CI/CD pipelines for AI systems Preferred Qualifications: Experience developing systems that generate production-ready code Familiarity with retrieval-augmented generation (RAG) techniques Experience with vector databases (Pinecone, Weaviate, etc.) Knowledge of containerization technologies (Docker, Kubernetes) Experience with model optimization, quantization, and efficient inference Contributions to open-source AI projects or research publications Familiarity with physical security or identity access management domains Experience implementing AI systems with strong security and governance controls This position offers the opportunity to work at the forefront of AI engineering, developing systems that not only generate code but also function autonomously to deliver real business R&D Ghaziabad, India

About Us - Attentive.ai is a leading provider of landscape and property management software powered by cutting-edge Artificial Intelligence (AI). Our software is designed to optimize workflows and help businesses scale up effortlessly in the outdoor services industry. Our Automeasure software caters to landscaping, snow removal, paving maintenance, and facilities maintenance businesses. We are also building Beam AI , an advanced AI engine focused on automating construction take-off and estimation workflows through deep AI. Beam AI is designed to extract intelligence from complex construction drawings, helping teams save time, reduce errors, and increase bid efficiency. Trusted by top US and Canadian sales teams, we are backed by renowned investors such as Sequoia Surge and InfoEdge Ventures." Position Description As a Research Engineer-II, you will be an integral part of our AI research team focused on transforming the construction industry through cutting-edge deep learning, computer vision and NLP technologies. You will contribute to the development of intelligent systems for automated construction take-off and estimation by working with unstructured data such as blueprint, drawings (including SVGs), and PDF documents. In this role, you will support the end-to-end lifecycle of AI-based solutions — from prototyping and experimentation to deployment in production. Your contributions will directly impact the scalability, accuracy, and efficiency of our products. Roles & Responsibilities Contribute to research and development initiatives focused on Computer Vision, Image Processing, and Deep Learning applied to construction-related data. Build and optimize models for extracting insights from documents such as blueprints, scanned PDFs, and SVG files. Contribute development of multi-modal models that integrate vision with language-based features (NLP/LLMs). Follow best data science and machine learning practices, including data-centric development, experiment tracking, model validation, and reproducibility. Collaborate with cross-functional teams including software engineers, ML researchers, and product teams to convert research ideas into real-world applications. Write clean, scalable, and production-ready code using Python and frameworks like PyTorch, TensorFlow, or HuggingFace. Stay updated with the latest research in computer vision and machine learning and evaluate applicability to construction industry challenges. Skills & Requirements 3–5 years of experience in applied AI/ML and research with a strong focus on Computer Vision and Deep Learning. Solid understanding of image processing, visual document understanding, and feature extraction from visual data. Familiarity with SVG graphics, NLP, or LLM-based architectures is a plus. Deep understanding of unsupervised learning techniques like clustering, dimensionality reduction, and representation learning. Proficiency in Python and ML frameworks such as PyTorch, OpenCV, TensorFlow, and HuggingFace Transformers. Hands-on experience with model optimization techniques (e.g., quantization, pruning, knowledge distillation). - Good to have Experience with version control systems (e.g., Git), project tracking tools (e.g., JIRA), and cloud environments (GCP, AWS, or Azure). Familiarity with Docker, Kubernetes, and containerized ML deployment pipelines. Strong analytical and problem-solving skills with a passion for building innovative solutions; ability to rapidly prototype and iterate. Comfortable working in a fast-paced, agile, startup-like environment with excellent communication and collaboration skills. Why Work With Us? Be part of a visionary team building a first-of-its-kind AI solution for the construction industry. Exposure to real-world AI deployment and cutting-edge research in vision and multimodal learning. Culture that encourages ownership, innovation, and growth. Opportunities for fast learning, mentorship, and career progression.

Job Description We aim to bring about a new paradigm in medical image diagnostics; providing intelligent, holistic, ethical, explainable and patient centric care. We are looking for innovative problem solvers who love solving problems. We want people who can empathize with the consumer, understand business problems, and design and deliver intelligent products. People who are looking to extend artificial intelligence into unexplored areas. Your primary focus will be in applying deep learning and artificial intelligence techniques to the domain of medical image analysis. Responsibilities Selecting features, building and optimizing classifier engines using deep learning techniques. Understanding the problem and applying the suitable image processing techniques Use techniques from artificial intelligence/deep learning to solve supervised and unsupervised learning problems. Understanding and designing solutions for complex problems related to medical image analysis by using Deep Learning/Object Detection/Image Segmentation. Recommend and implement best practices around the application of statistical modeling. Create, train, test, and deploy various neural networks to solve complex problems. Develop and implement solutions to fit business problems which may include applying algorithms from a standard statistical tool, deep learning or custom algorithm development. Understanding the requirements and designing solutions and architecture in accordance with them. Participate in code reviews, sprint planning, and Agile ceremonies to drive high-quality deliverables. Design and implement scalable data science architectures for training, inference, and deployment pipelines. Ensure code quality, readability, and maintainability by enforcing software engineering best practices within the data science team. Optimize models for production, including quantization, pruning, and latency reduction for real-time inference. Drive the adoption of versioing strategies for models, datasets, and experiments (e.g., using MLFlow, DVC). Contribute to the architectural design of data platforms to support large-scale experimentation and production workloads. Skills and Qualifications Strong software engineering skills in Python (or other languages used in data science) with emphasis on clean code, modularity, and testability. Excellent understanding and hands-on of Deep Learning techniques such as ANN, CNN, RNN, LSTM, Transformers, VAEs etc. Must have experience with Tensorflow or PyTorch framework in building, training, testing, and deploying neural networks. Experience in solving problems in the domain of Computer Vision. Knowledge of data, data augmentation, data curation, and synthetic data generation. Ability to understand the complete problem and design the solutions that best fit all the constraints. Knowledge of the common data science and deep learning libraries and toolkits such as Keras, Pandas, Scikit-learn, Numpy, Scipy, OpenCV etc. Good applied statistical skills, such as distributions, statistical testing, regression, etc. Exposure to Agile/Scrum methodologies and collaborative development practices. Experience with the development of RESTful APIs. The knowledge of libraries like FastAPI and the ability to apply it to deep learning architectures is essential. Excellent analytical and problem-solving skills with a good attitude and keen to adapt to evolving technologies. Experience with medical image analysis will be an advantage. Experience designing and building ML architecture components (e.g., feature stores, model registries, inference servers). Solid understanding of software design patterns, microservices, and cloud-native architectures. Expertise in model optimization techniques (e.g., ONNX conversion, TensorRT, model distillation) Education: BE/B Tech MS/M Tech (will be a bonus) Experience: 3-5 Years

🚀 Job Title: AI Engineer (Full Stack / Model Deployment Specialist) Location: Remote (India preferred) Type: Full-Time (6-Month Fixed Contract) Experience Level: 1+ Years Salary: Competitive (based on experience) Potential: High-performing candidates may be offered a permanent role after the contract 🧩 About Us We are a dynamic collaboration between Funding Bay , Effer Ventures , and FBX Capital Partners, three industry leaders combining forces to deliver financial, compliance, and strategic growth solutions to businesses across the UK. We’re looking for an AI Engineer who can bridge the gap between machine learning and production-ready applications. If you love optimizing models, deploying them in real-world environments, and know your way around modern web stacks, this role is for you. 🔧 What You’ll Do End-to-End Ownership of ML Models: From training and evaluation to optimization and deployment. Deploy ML Models using AWS services (EC2, Lambda, S3, SageMaker, or custom Docker setups). Optimize Model Performance: Ensure fast inference, low memory usage, and high-quality results. Integrate AI into MERN Stack Applications: Build APIs and interfaces to expose your models to the frontend. Collaborate Cross-Functionally with frontend, product, and design teams. Build scalable and secure pipelines for data ingestion, model serving, and monitoring. Optimize for Speed & Usability : Ensure both backend inference and frontend UI are responsive and seamless. ✅ What We’re Looking For Proficient in MERN Stack (MongoDB, Express.js, React, Node.js) Strong Python skills , especially for AI/ML (NumPy, Pandas, scikit-learn, TensorFlow or PyTorch etc) Hands-on with Model Optimization : Quantization, pruning, distillation, or ONNX deployment is a plus Solid AWS Experience: EC2, S3, IAM, Lambda, API Gateway, CloudWatch, etc. Experience with Docker & CI/CD pipelines (e.g., GitHub Actions, Jenkins) Comfortable building and consuming REST/GraphQL APIs Familiar with ML deployment tools like FastAPI, Flask, TorchServe, or SageMaker endpoints Good understanding of performance profiling, logging, and model monitoring ⭐ Nice to Have Experience with LangChain , LLMs , or NLP pipelines Startup or fast-paced team background Open-source contributions or live-deployed AI projects 🌱 Why Join Us? Build & deploy real AI products that go live Work in a growth-focused, high-ownership environment 6-month contract with the potential for a Permanent full-time Flexible work culture & flat hierarchy Learn fast and build faster with founders and builders Take ownership of core parts of the AI stack Competitive compensation based on experience 📬 To Apply Send us: Your resume A link to your GitHub or portfolio A short paragraph about a project where you deployed an optimized AI model 📧 Email: developer@fundingbay.co.uk or directly apply

We’re Hiring: Senior AI Developer Remote | Full-time | TechGratia We're solving real-world problems with cutting-edge AI. If you're skilled in LLMs, Generative AI , and deploying scalable models—this is your chance to make real impact. Build AI solutions using LLMs & GenAI frameworks Fine-tune models for domain-specific needs Deploy/manage LLMs with Azure OpenAI Work with CNNs, RNNs , NLP & multimodal tasks Write clean, modular, production-ready code Strong Python, PyTorch/TensorFlow, Hugging Face Experience with GPT, LLaMA, Mistral , Azure OpenAI, AWS Deep learning knowledge: CNN, RNN, Attention Familiarity with LangChain, RAG, vector DBs Hands-on with fine-tuning, quantization, ML workflows Join a collaborative team building AI that matters. 📩 Apply: sheethal.cs@techgratia.com #Hiring #AIJobs #LLM #GenerativeAI #RemoteJobs #TechGratia

Job purpose: Design, develop, and deploy end-to-end AI/ML systems, focusing on large language models (LLMs), prompt engineering, and scalable system architecture. Leverage technologies such as Java/Node.js/NET to build robust, high-performance solutions that integrate with enterprise systems. Who You Are: Education: Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field. PhD is a plus. 5+ years of experience in AI/ML development, with at least 2 years working on LLMs or NLP. Proven expertise in end-to-end system design and deployment of production-grade AI systems. Hands-on experience with Java/Node.js/.NET for backend development. Proficiency in Python and ML frameworks (TensorFlow, PyTorch, Hugging Face Transformers). Key Responsibilities: 1. Model Development & Training: Design, train, and fine-tune large language models (LLMs) for tasks such as natural language understanding, generation, and classification. Implement and optimize machine learning algorithms using frameworks like TensorFlow, PyTorch, or Hugging Face. 2. Prompt Engineering: Craft high-quality prompts to maximize LLM performance for specific use cases, including chatbots, text summarization, and question-answering systems. Experiment with prompt tuning and few-shot learning techniques to improve model accuracy and efficiency. 3. End-to-End System Design: Architect scalable, secure, and fault-tolerant AI/ML systems, integrating LLMs with backend services and APIs. Develop microservices-based architectures using Java/Node.js/.NET for seamless integration with enterprise applications. Design and implement data pipelines for preprocessing, feature engineering, and model inference. 4. Integration & Deployment: Deploy ML models and LLMs to production environments using containerization (Docker, Kubernetes) and cloud platforms (AWS/Azure/GCP). Build RESTful or GraphQL APIs to expose AI capabilities to front-end or third-party applications. 5. Performance Optimization: Optimize LLMs for latency, throughput, and resource efficiency using techniques like quantization, pruning, and model distillation. Monitor and improve system performance through logging, metrics, and A/B testing. 6. Collaboration & Leadership: Work closely with data scientists, software engineers, and product managers to align AI solutions with business objectives. Mentor junior engineers and contribute to best practices for AI/ML development. What will excite us: Strong understanding of LLM architectures and prompt engineering techniques. Experience with backend development using Java/Node.js (Express)/.NET Core. Familiarity with cloud platforms (AWS, Azure, GCP) and DevOps tools (Docker, Kubernetes, CI/CD). Knowledge of database systems (SQL, NoSQL) and data pipeline tools (Apache Kafka, Airflow). Strong problem-solving and analytical skills. Excellent communication and teamwork abilities. Ability to work in a fast-paced, collaborative environment. What will excite you: Lead AI innovation in a fast-growing, technology-driven organization. Work on cutting-edge AI solutions, including LLMs, autonomous AI agents, and Generative AI applications. Engage with top-tier enterprise clients and drive AI transformation at scale. Location: Ahmedabad

Compensation: INR 50 lacs-1cr (INR 30-50 lacs pa plus stocks worth a similar amount) Strictly please do NOT apply if you have not done at least 4 years of programming and have not worked on data projects that have high volume data and have not worked on product development. Preferred location is Hyderabad we are open to people who want later to be at Noida. Multiplier AI is a leader in AI accelerators for life sciences and is due for listing. About the Role We are seeking a seasoned and forward-thinking AI Product Development Manager to spearhead AI data cloud implementation projects across enterprise and industry-specific use cases. This is a high-impact leadership role that combines deep technical expertise with strategic consulting to deliver scalable, efficient, and secure data wrangling product solutions. This will include work on agentic and other AI technicalities. Key Responsibilities Lead end-to-end design and deployment of data platforms in production environments. Define architecture for on-device or private-cloud data deployments, optimizing for latency, token cost, and privacy. Collaborate with cross-functional teams (data, MLOps, product, security) to integrate into existing systems and workflows. Data extraction and transformation leadership Mentor engineering and data science teams on best practices in efficient prompt engineering, RAG pipelines, quantization, and distillation techniques. Act as a thought partner to leadership and clients on GenAI roadmap, risk management, and responsible AI design. Required Skills & Experience Proven experience in bbuilding data extraction and transformation projects in production preferably using LLMs and NLP techniques. this is essential do not apply if not done it Strong understanding of transformer architecture, tokenizer design, and parameter-efficient fine-tuning (LoRA, QLoRA). Hands-on with informatica Realtio and data management optimization techniques. Experience integrating SLMs into real-world systems—mobile apps, secure enterprise workflows, or embedded devices. Background in Python, PyTorch/TensorFlow, and familiarity with Data ops tools Ships product faster Preferred Qualifications Prior consulting experience with AI/ML deployments in pharma, finance, or regulated sectors. Familiarity with privacy-preserving AI, federated learning, or differential privacy. Contributions to data ETL projects What We Offer Leadership in shaping the future of lightweight AI. Exposure to cutting-edge GenAI applications across industries. Competitive compensation and equity options (for permanent roles).

Roles & Responsibilities Design, implement, and train deep learning models for: Text-to-Speech (e.g., SpeechT5, StyleTTS2, YourTTS, XTTS-v2 or similar models) Voice Cloning with speaker embeddings (x-vectors, d-vectors), few-shot adaptation, prosody and emotion transfer Engineer multilingual audio-text preprocessing pipelines: Text normalization, grapheme-to-phoneme (G2P) conversion, Unicode normalization (NFC/NFD) Silence trimming, VAD-based audio segmentation, audio enhancement for noisy corpora, speech prosody modification and waveform manipulation Build scalable data loaders using PyTorch for: Large-scale, multi-speaker datasets with variable-length sequences and chunked streaming Extract and process acoustic features: Log-mel spectrograms, pitch contours, MFCCs, energy, speaker embeddings Optimize training using: Mixed precision (FP16/BFloat16), gradient checkpointing, label smoothing, quantization-aware training Build serving infrastructure for inference using: TorchServe, ONNX Runtime, Triton Inference Server, FastAPI (for REST endpoints), including batch and real-time modes Optimize models for production: Quantization, model pruning, ONNX conversion, parallel decoding, GPU/CPU memory profiling Create automated and human evaluation logics: MOS, PESQ, STOI, BLEU, WER/CER, multi-speaker test sets, multilingual subjective listening tests Implement ethical deployment safeguards: Digital watermarking, impersonation detection, and voice verification for cloned speech Conduct literature reviews and reproduce state-of-the-art papers; adapt and improve on open benchmarks Mentor junior contributors, review code, and maintain shared research and model repositories Collaborate across teams (MLOps, backend, product, linguists) to translate research into deployable, user-facing solutions Required Skills Advanced proficiency in Python and PyTorch (TensorFlow a plus) Strong grasp of deep learning concepts: Sequence-to-sequence models, Transformers, autoregressive and non-autoregressive decoders, attention mechanisms, VAEs, GANs Experience with modern speech processing toolkits: ESPnet, NVIDIA NeMo, Coqui TTS, OpenSeq2Seq, or equivalent Design custom loss function for custom models based on: Mel loss, GAN loss, KL divergence, attention losses, etc.,, learning rate schedules, training stability Hands-on experience with multilingual and low-resource language modeling Understanding of transformer architecture, LLMs and working with existing AI models, tools and APIs Model serving & API integration: TorchServe, FastAPI, Docker, ONNX Runtime Preferred (Bonus) Skills CUDA kernel optimization, custom GPU operations, memory footprint profiling Experience deploying on AWS/GCP with GPU acceleration Experience developing RESTful APIs for real-time TTS/voice cloning endpoints Publications or open-source contributions in TTS, ASR, or speech processing Working knowledge of multilingual translation pipelines Knowledge of speaker diarization, voice anonymization, and speech synthesis for agglutinative/morphologically rich languages Milestones & Expectations (First 3–6 Months) Deliver at least one production-ready TTS or Voice Cloning model integrated with India Speaks’ Dubbing Studio or SaaS APIs Create a fully reproducible experiment pipeline for multilingual speech modeling, complete with model cards and performance benchmarks Contribute to custom evaluation tools for measuring quality across Indian languages Deploy optimized models to live staging environments using Triton, TorchServe, or ONNX Demonstrate impact through real-world integration in education, media, or defence deployments

Institute of Information Science Postdoctoral Researcher 2 Person The Computer Systems Laboratory - Machine Learning Systems Team Focuses On Research Areas Including Parallel And Distributed Computing, Compilers, And Computer Architecture. We Aim To Leverage Computer System Technologies To Accelerate The Inference And Training Of Deep Learning Models And Develop Optimizations For Next-generation AI Models. Our Research Emphasizes The Following Job Description Unit Institute of Information Science JobTitle Postdoctoral Researcher 2 Person Work Content Research on Optimization of Deep Learning Model Inference and Training AI Model Compression and Optimization Model Compression Techniques (e.g., Pruning And Quantization) Reduce The Size And Computational Demands Of AI Models, Which Are Crucial For Resource-constrained Platforms Such As Embedded Systems And Memory-limited AI Accelerators. We Aim To Explore AI compiler: deployment methods for compressed models across servers, edge devices, and heterogeneous systems. High performance computing: efficient execution of compressed models on processors with advanced AI extensions, e.g., Intel AVX512, ARM SVE, RISC-V RVV, and tensor-level accelerations on GPUs and NPUs. AI Accelerator Design We aim to design AI accelerators for accelerating AI model inference, focusing on software and hardware co-design and co-optimization. Optimization of AI Model Inference in Heterogeneous Environments Computer Architectures Are Evolving Toward Heterogeneous Multi-processor Designs (e.g., CPUs + GPUs + AI Accelerators). Integrating Heterogeneous Processors To Execute Complex Models (e.g., Hybrid Models, Multi-models, And Multi-task Models) With High Computational Efficiency Poses a Critical Challenge. We Aim To Explore Efficient scheduling algorithms. Parallel algorithms for the three dimensions: data parallelism, model parallelism, and tensor parallelism. Qualifications Ph.D. degree in Computer Science, Computer Engineering, or Electrical Engineering Experience in parallel computing and parallel programming (CUDA or OpenCL, C/C++ programming) or hardware design (Verilog or HLS) Proficient in system and software development Candidates With The Following Experience Will Be Given Priority Experience in deep learning platforms, including PyTorch, TensorFlow, TVM, etc. Experience in high-performance computing or embedded systems. Experience in algorithm designs. Knowledge of compilers or computer architecture Working Environment Operating Hours 8:30AM-5:30PM Work Place Institute of Information Science, Academia Sinica Treatment According to Academia Sinica standards: Postdoctoral Researchers: NT$64,711-99,317/month. Benefits include: labor and healthcare insurance, and year-end bonuses. Reference Site 洪鼎詠網頁: http://www.iis.sinica.edu.tw/pages/dyhong/index_zh.html, 吳真貞網頁: http://www.iis.sinica.edu.tw/pages/wuj/index_zh.html Please Email Your CV (including Publications, Projects, And Work Experience), Transcripts (undergraduate And Above), And Any Other Materials That May Assist In The Review Process To The Following PIs Acceptance Method Contacts Dr. Ding-Yong Hong Contact Address Room 818, New IIS Building, Academia Sinica Contact Telephone 02-27883799 ext. 1818 Email dyhong@iis.sinica.edu.tw Required Documents Dr. Ding-Yong Hong: dyhong@iis.sinica.edu.tw Dr. Jan-Jan Wu: wuj@iis.sinica.edu.tw Precautions for application Date Publication Date 2025-01-20 Expiration Date 2025-12-31

About Us Yubi stands for ubiquitous. But Yubi will also stand for transparency, collaboration, and the power of possibility. From being a disruptor in India’s debt market to marching towards global corporate markets from one product to one holistic product suite with seven products Yubi is the place to unleash potential. Freedom, not fear. Avenues, not roadblocks. Opportunity, not obstacles. About Yubi Yubi, formerly known as CredAvenue, is re-defining global debt markets by freeing the flow of finance between borrowers, lenders, and investors. We are the world's possibility platform for the discovery, investment, fulfillment, and collection of any debt solution. At Yubi, opportunities are plenty and we equip you with tools to seize it. In March 2022, we became India's fastest fintech and most impactful startup to join the unicorn club with a Series B fundraising round of $137 million. In 2020, we began our journey with a vision of transforming and deepening the global institutional debt market through technology. Our two-sided debt marketplace helps institutional and HNI investors find the widest network of corporate borrowers and debt products on one side and helps corporates to discover investors and access debt capital efficiently on the other side. Switching between platforms is easy, which means investors can lend, invest and trade bonds - all in one place. All of our platforms shake up the traditional debt ecosystem and offer new ways of digital finance. Yubi Credit Marketplace - With the largest selection of lenders on one platform, our credit marketplace helps enterprises partner with lenders of their choice for any and all capital requirements. Yubi Invest - Fixed income securities platform for wealth managers & financial advisors to channel client investments in fixed income Financial Services Platform - Designed for financial institutions to manage co-lending partnerships & asset based securitization Spocto - Debt recovery & risk mitigation platform Corpository - Dedicated SaaS solutions platform powered by Decision-grade data, Analytics, Pattern Identifications, Early Warning Signals and Predictions to Lenders, Investors and Business Enterprises So far, we have on-boarded over 17000+ enterprises, 6200+ investors & lenders and have facilitated debt volumes of over INR 1,40,000 crore. Backed by marquee investors like Insight Partners, B Capital Group, Dragoneer, Sequoia Capital, LightSpeed and Lightrock, we are the only-of-its-kind debt platform globally, revolutionizing the segment. At Yubi, People are at the core of the business and our most valuable assets. Yubi is constantly growing, with 1000+ like-minded individuals today, who are changing the way people perceive debt. We are a fun bunch who are highly motivated and driven to create a purposeful impact. Come, join the club to be a part of our epic growth story. About The Role We're looking for a highly skilled, results-driven AI Developer who thrives in fast-paced, high-impact environments. If you are passionate about pushing the boundaries of Computer Vision, OCR, NLP and and Large Language Models (LLMs) and have a strong foundation in building and deploying AI solutions, this role is for you. As a Lead Data Scientist, you will take ownership of designing and implementing state-of-the-art AI products. This role demands deep technical expertise, the ability to work autonomously, and a mindset that embraces complex challenges head-on. Here, you won't just fine-tune pre-trained models—you'll be architecting, optimizing, and scaling AI solutions that power real-world applications. Key Responsibilities Architect, develop, and deploy high-performance AI Solutions for real-world applications. Implement and optimize state-of-the-art LLM , OCR models and frameworks. Fine-tune and integrate LLMs (GPT, LLaMA, Mistral, etc.) to enhance text understanding and automation. Build and optimize end-to-end AI pipelines, ensuring efficient data processing and model deployment. Work closely with engineers to operationalize AI models in production (Docker, FastAPI, TensorRT, ONNX). Enhance GPU performance and model inference efficiency, applying techniques such as quantization and pruning. Stay ahead of industry advancements, continuously experimenting with new AI architectures and training techniques. Work in a highly dynamic, startup-like environment, balancing rapid experimentation with production-grade robustness. What We're Looking For Requirements Required Skills & Qualifications: Proven technical expertise – Strong programming skills in Python, PyTorch, TensorFlow with deep experience in NLP and LLM Hands-on experience in developing, training, and deploying LLM and Agentic workflows Strong background in vector databases, RAG pipelines, and fine-tuning LLMs for document intelligence. Deep understanding of Transformer-based architectures for vision and text processing. Experience working with Hugging Face, OpenCV, TensorRT, and NVIDIA GPUs for model acceleration. Autonomous problem solver – You take initiative, work independently, and drive projects from research to production. Strong experience in scaling AI solutions, including model optimization and deployment on cloud platforms (AWS/GCP/Azure). Thrives in fast-paced environments – You embrace challenges, pivot quickly, and execute effectively. Familiarity with MLOps tools (Docker, FastAPI, Kubernetes) for seamless model deployment. Experience in multi-modal models (Vision + Text). Good to Have Financial background and understanding corporate finance . Contributions to open-source AI projects.

Overview - We are hiring experienced AI Developers to lead the design, development, and scaling of intelligent systems using large language models (LLMs). This includes building prompt-based agents, developing and fine-tuning custom AI models, and architecting advanced pipelines across various business functions. You will work across the full AI development lifecycle—from prompt engineering to model training and deployment—while staying at the forefront of innovation in generative AI and autonomous agent frameworks. Key Responsibilities: - Design and deploy intelligent agents using LLMs such as OpenAI GPT-4, Claude, Mistral, Gemini, Cohere, etc. Build prompt-driven and autonomous agents using frameworks like LangChain, AutoGen, CrewAI, Semantic Kernel, LlamaIndex , or custom stacks. Architect and implement multi-agent systems capable of advanced reasoning, coordination, and tool interaction. Incorporate goal-setting, sub-task decomposition, and autonomous feedback loops for agent self-improvement. Develop custom AI models via fine-tuning, supervised learning , or LoRA/QLoRA approaches using Hugging Face Transformers, PyTorch , or TensorFlow . Build and manage Retrieval-Augmented Generation (RAG) pipelines with vector databases like Pinecone, FAISS, Weaviate, or Chroma. Train and evaluate models on custom datasets using modern NLP workflows and distributed training tools. Optimize models for latency, accuracy, and cost efficiency in both prototype and production environments. Create and maintain testing and evaluation pipelines for prompt quality, hallucination detection, and model behavior safety. Integrate external tools, APIs, plugins, and knowledge bases to enhance agent capabilities. Collaborate with product and engineering teams to translate use cases into scalable AI solutions. Required Technical Skills: - 3+ years hands-on experience with large language models, generative AI, conversational systems, or agent-based system development. Proficient in Python , with experience in AI/ML libraries such as Transformers, LangChain, PyTorch, TensorFlow, PEFT , and Scikit-learn. Strong understanding of prompt engineering, instruction tuning , and system prompt architecture. Experience with custom model training, fine-tuning , and deploying models via Hugging Face, OpenAI APIs, or open-source LLMs. Experience designing and implementing RAG pipelines and managing embedding stores. Familiarity with agent orchestration frameworks , tool integration, memory handling, and context management. Working knowledge of containerization (Docker), MLOps , and cloud environments (AWS, GCP, Azure). Preferred Experience: - Exposure to distributed training (DeepSpeed, Accelerate), quantization , or model optimization techniques . Familiarity with LLM evaluation tools (Trulens, LM Eval Harness, custom eval agents). Experience with RLHF, multi-modal models , or voice/chat integrations . Background in data engineering for building high-quality training/evaluation datasets. Experience with self-healing agents, auto-reflection loops, and adaptive control systems . Shift Timing: Night Shift (Fixed timing will be disclosed at the time of joining) Show more Show less

Job Category: AIML Job Type: Full Time Job Location: Bengaluru Mangalore Experience: 4-8 Years Skills: AI AWS/AZURE/GCP Azure ML C computer vision data analytics Data Modeling Data Visualization deep learning Descriptive Analytics GenAI Image processing Java LLM models ML ONNX Predictive Analytics Python R Regression/Classification Models SageMaker SQL TensorFlow Position Overview We are looking for an experienced AI/ML Engineer to join our team in Bengaluru. The ideal candidate will bring a deep understanding of machine learning, artificial intelligence, and big data technologies, with proven expertise in developing scalable AI/ML solutions. You will lead technical efforts, mentor team members, and collaborate with cross-functional teams to design, develop, and deploy cutting edge AI/ML applications. Job Details Job Category: AI/ML Engineer. Job Type: Full-Time Job Location: Bengaluru Experience Required: 4-8 Years About Us We are a multi-award-winning creative engineering company. Since 2011, we have worked with our customers as a design and technology enablement partner, guiding them on their digital transformation journeys. Roles And Responsibilities Design, develop, and deploy deep learning models for object classification, detection, and segmentation using CNNs and Transfer Learning. Implement image preprocessing and advanced computer vision pipelines. Optimize deep learning models using pruning, quantization, and ONNX for deployment on edge devices. Work with PyTorch, TensorFlow, and ONNX frameworks to develop and convert models. Accelerate model inference using GPU programming with CUDA and cuDNN. Port and test models on embedded and edge hardware platforms. ( Orin, Jetson, Hailo ) Conduct research and experiments to evaluate and integrate GenAI technologies in computer vision tasks. Explore and implement cloud-based AI workflows, particularly using AWS/Azure AI/ML services. Collaborate with cross-functional teams for data analytics, data processing, and large-scale model training. Required Skills Strong programming experience in Python. Solid background in deep learning, CNNs, and transfer learning and Machine learning basics. Expertise in object detection, classification, segmentation. Proficiency with PyTorch, TensorFlow, and ONNX. Experience with GPU acceleration (CUDA, cuDNN). Hands-on knowledge of model optimization (pruning, quantization). Experience deploying models to edge devices (e.g., Jetson, mobile, Orin, Hailo ) Understanding of image processing techniques. Familiarity with data pipelines, data preprocessing, and data analytics. Willingness to explore and contribute to Generative AI and cloud-based AI solutions. Good problem-solving and communication skills. Preferred (Nice-to-Have) Experience with C/C++. Familiarity with AWS Cloud AI/ML tools (e.g., SageMaker, Rekognition). Exposure to GenAI frameworks like OpenAI, Stable Diffusion, etc. Knowledge of real-time deployment systems and streaming analytics. Qualifications Graduation/Post-graduation in Computers, Engineering, or Statistics from a reputed institute. What We Offer Competitive salary and benefits package. Opportunity to work in a dynamic and innovative environment. Professional development and learning opportunities. Visit us on: CodeCraft Technologies LinkedIn : CodeCraft Technologies LinkedIn Instagram : CodeCraft Technologies Instagram Show more Show less

Organization: At CommBank, we never lose sight of the role we play in other people’s financial wellbeing. Our focus is to help people and businesses move forward to progress. To make the right financial decisions and achieve their dreams, targets, and aspirations. Regardless of where you work within our organisation, your initiative, talent, ideas, and energy all contribute to the impact that we can make with our work. Together we can achieve great things. Job Title: Data Scientist Location: Bangalore Business & Team: BB Advanced Analytics and Artificial Intelligence COE Impact & contribution: As a Senior Data Scientist, you will be instrumental in pioneering Gen AI and multi-agentic systems at scale within CommBank. You will architect, build, and operationalize advanced generative AI solutions—leveraging large language models (LLMs), collaborative agentic frameworks, and state-of-the-art toolchains. You will drive innovation, helping set the organizational strategy for advanced AI, multi-agent collaboration, and responsible next-gen model deployment. Roles & Responsibilities: Gen AI Solution Development: Lead end-to-end development, fine-tuning, and evaluation of state-of-the-art LLMs and multi-modal generative models (e.g., transformers, GANs, VAEs, Diffusion Models) tailored for financial domains. Multi-Agentic System Engineering: Architect, implement, and optimize multi-agent systems, enabling swarms of AI agents (utilizing frameworks like Lang chain, Lang graph, and MCP) to dynamically collaborate, chain, reason, critique, and autonomously execute tasks. LLM-Backed Application Design: Develop robust, scalable GenAI-powered APIs and agent workflows using Fast API, Semantic Kernel, and orchestration tools. Integrate observability and evaluation using Lang fuse for tracing, analytics, and prompt/response feedback loops. Guardrails & Responsible AI: Employ frameworks like Guardrails AI to enforce robust safety, compliance, and reliability in LLM deployments. Establish programmatic checks for prompt injections, hallucinations, and output boundaries. Enterprise-Grade Deployment: Productionize and manage at-scale Gen AI and agent systems with cloud infrastructure (GCP/AWS/Azure), utilizing model optimization (quantization, pruning, knowledge distillation) for latency/throughput trade offs. Toolchain Innovation: Leverage and contribute to open source projects in the Gen AI ecosystem (e.g., Lang Chain, Lang Graph, Semantic Kernel, Lang fuse, Hugging face, Fast API). Continuously experiment with emerging frameworks and research. Stakeholder Collaboration: Partner with product, engineering, and business teams to define high-impact use cases for Gen AI and agentic automation; communicate actionable technical strategies and drive proof-of-value experiments into production. Mentorship & Thought Leadership: Guide junior team members in best practices for Gen AI, prompt engineering, agentic orchestration, responsible deployment, and continuous learning. Represent CommBank in the broader AI community through papers, patents, talks, and open-source. Essential Skills: 6+ years of hands-on experience in Machine Learning, Deep Learning, or Generative AI domains, including practical expertise with LLMs, multi-agent frameworks, and prompt engineering. Proficient in building and scaling multi-agent AI systems using Lang Chain, Lang Graph, Semantic Kernel, MCP, or similar agentic orchestration tools. Advanced experience developing and deploying Gen AI APIs using Fast API; operational familiarity with Lang fuse for LLM evaluation, tracing, and error analytics. Demonstrated ability to apply Guardrails to enforce model safety, explainability, and compliance in production environments. Experience with transformer architectures (BERT/GPT, etc.), fine-tuning LLMs, and model optimization (distillation/quantization/pruning). Strong software engineering background (Python), with experience in enterprise-grade codebases and cloud-native AI deployments. Experience integrating open and commercial LLM APIs and building retrieval-augmented generation (RAG) pipelines. Exposure to agent-based reinforcement learning, agent simulation, and swarm-based collaborative AI. Familiarity with robust experimentation using tools like Lang Smith, GitHub Copilot, and experiment tracking systems. Proven track record of driving Gen AI innovation and adoption in cross-functional teams. Papers, patents, or open-source contributions to the Gen AI/LLM/Agentic AI ecosystem. Experience with financial services or regulated industries for secure and responsible deployment of AI. Education Qualifications: Bachelor’s or Master’s degree in Computer Science, Engineering, Information Technology. If you're already part of the Commonwealth Bank Group (including Bankwest, x15ventures), you'll need to apply through Sidekick to submit a valid application. We’re keen to support you with the next step in your career. We're aware of some accessibility issues on this site, particularly for screen reader users. We want to make finding your dream job as easy as possible, so if you require additional support please contact HR Direct on 1800 989 696. Advertising End Date: 01/07/2025 Show more Show less

AI Engineer Key Responsibilities GenAI Development: Design and develop advanced GenAI models (e.g., LLMs, DALL E models) and AI Agents to automate internal tasks and workflows. Exposure to LLMs: Utilize Azure Open AI APIs, experience on models like GPT4o, O3 , llama3 Enhance the existing RAG based application: In depth understanding of stages of RAG - chunking, retrieval etc. Cloud Deployment: Deploy and scale GenAI solutions on Azure Cloud services (e.g., Azure Function App) for optimal performance. In depth understanding of ML models like linear regression, random forest, decision trees. In depth understanding on clustering and supervised models. AI Agent Development: Build AI agents using frameworks like LangChain to streamline internal processes and boost efficiency. Data Analytics: Perform advanced data analytics to preprocess datasets, evaluate model performance, and derive actionable insights for GenAI solutions. Data Visualization: Create compelling visualizations (e.g., dashboards, charts) to communicate model outputs, performance metrics, and business insights to stakeholders. Stakeholder Collaboration: Partner with departments to gather requirements, align on goals, and present technical solutions and insights effectively to non-technical stakeholders. Model Optimization: Fine-tune GenAI models for efficiency and accuracy using techniques like prompt engineering, quantization, and RAG (Retrieval-Augmented Generation). LLMOps Best Practices: Implement GenAI-specific MLOps, including CI/CD pipelines (Git, Azure DevOps) Leadership: Guide cross-functional teams, mentor junior engineers, and drive project execution with strategic vision and ownership. Helicopters, strategic Thinking**: Develop innovative GenAI strategies to address business challenges, leveraging data insights to align solutions with organizational goals. Self-Driven Execution: Independently lead projects to completion with minimal supervision, proactively resolving challenges and seeking collaboration when needed. Continuous Learning: Stay ahead of GenAI, analytics, and visualization advancements, self-learning new techniques to enhance project outcomes. Required Skills & Experience Experience: 8-12 years in AI/ML development, with at least 4 years focused on Generative AI and AI agent frameworks. Education: BTech/BE in Computer Science, Engineering, or equivalent (Master’s or PhD in AI/ML is a plus). Programming: Expert-level Python proficiency, with deep expertise in GenAI libraries (e.g., LangChain, Hugging Face Transformers, PyTorch, Open AI SDK) and data analytics libraries (e.g., Pandas, NumPy), sk-learn. Mac Data Analytics: Strong experience in data preprocessing, statistical analysis, and model evaluation to support GenAI development and business insights. Data Visualization: Proficiency in visualization tools (e.g., Matplotlib, Seaborn, Plotly, Power BI, or Tableau) to create dashboards and reports for stakeholders. Azure Cloud Expertise: Strong experience with Azure Cloud services (e.g., Azure Function App, Azure ML, serverless) for model training and deployment. GenAI Methodologies: Deep expertise in LLMs, AI agent frameworks, prompt engineering, and RAG for internal workflow automation. Deployment: Proficiency in Docker, Kubernetes, and CI/CD pipelines (e.g., Azure DevOps, GitHub Actions) for production-grade GenAI systems. LLMOps: Expertise in GenAI MLOps, including experiment tracking (e.g., Weights & Biases), automated evaluation metrics (e.g., BLEU, ROUGE), and monitoring. Soft Skills: Communication: Exceptional verbal and written skills to articulate complex GenAI concepts, analytics, and visualizations to technical and non-technical stakeholders. Strategic Thinking: Ability to align AI solutions with business objectives, using data-driven insights to anticipate challenges and propose long-term strategies. Problem-Solving: Strong analytical skills with a proactive, self-starter mindset to independently resolve complex issues. Collaboration: Collaborative mindset to work effectively across departments and engage colleagues for solutions when needed. Speed to outcome Preferred Skills Experience deploying GenAI models in production environments, preferably on Azure Familiarity with multi-agent systems, reinforcement learning, or distributed training (e.g., DeepSpeek). Knowledge of DevOps practices, including Git, CI/CD, and infrastructure-as-code. Advanced data analytics techniques (e.g., time-series analysis, A/B testing) for GenAI applications. Experience with interactive visualization frameworks (e.g., Dash, Streamlit) for real-time dashboards. Contributions to GenAI or data analytics open-source projects or publications in NLP, generative modeling, or data scien Show more Show less

Company: Qualcomm India Private Limited Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: Job Description Join the exciting Generative AI team at Qualcomm focused on integrating cutting edge GenAI models on Qualcomm chipsets. The team uses Qualcomm chips’ extensive heterogeneous computing capabilities to allow inference of GenAI models on-device without a need for connection to the cloud. Our inference engine is designed to help developers run neural network models trained in a variety of frameworks on Snapdragon platforms at blazing speeds while still sipping the smallest amount of power. Utilize this power efficient hardware and Software stack to run Large Language Models (LLMs) and Large Vision Models (LVM) at near GPU speeds! Responsibilities: In this role, you will spearhead the development and commercialization of the Qualcomm AI Runtime (QAIRT) SDK on Qualcomm SoCs. As an AI inferencing expert, you'll push the limits of performance from large models. Your mastery in deploying large C/C++ software stacks using best practices will be essential. You'll stay on the cutting edge of GenAI advancements, understanding LLMs/Transformers and the nuances of edge-based GenAI deployment. Most importantly, your passion for the role of edge in AI's evolution will be your driving force. Requirements: Master’s/Bachelor’s degree in computer science or equivalent. 2-4 years of relevant work experience in software development. Strong understanding of Generative AI models – LLM, LVM, LMMs and building blocks (self-attention, cross attention, kv caching etc.) Floating-point, Fixed-point representations and Quantization concepts. Experience with optimizing algorithms for AI hardware accelerators (like CPU/GPU/NPU). Strong in C/C++ programming, Design Patterns and OS concepts. Good scripting skills in Python. Excellent analytical and debugging skills. Good communication skills (verbal, presentation, written). Ability to collaborate across a globally diverse team and multiple interests. Preferred Qualifications Strong understanding of SIMD processor architecture and system design. Proficiency in object-oriented software development and familiarity Familiarity with Linux and Windows environment Strong background in kernel development for SIMD architectures. Familiarity with frameworks like llama.cpp, MLX, and MLC is a plus. Good knowledge of PyTorch, TFLite, and ONNX Runtime is preferred. Experience with parallel computing systems and languages like OpenCL and CUDA is a plus. Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field. 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers.

Company: Qualcomm India Private Limited Job Area: Engineering Group, Engineering Group > Systems Engineering General Summary: Summary - We are seeking experts with a robust background in the field of deep learning (DL) to design state-of-the-art low-level perception (LLP) as well as end-to-end AD models, with a focus on achieving accuracy-latency Pareto optimality. This role involves comprehending state-of-the-art research in this field and deploying networks on the Qualcomm Ride platform for L2/L3 Advanced Driver Assistance Systems (ADAS) and autonomous driving. The ideal candidate must be well-versed in recent advancements in Vision Transformers (Cross-attention, Self-attention), lifting 2D features to Bird's Eye View (BEV) space, and their applications to multi-modal fusion. This position offers extensive opportunities to collaborate with advanced R&D teams of leading automotive Original Equipment Manufacturers (OEMs) as well as Qualcomm's internal stack teams. The team is responsible for enhancing the speed, accuracy, power consumption, and latency of deep networks running on Snapdragon Ride AI accelerators. A thorough understanding of machine learning algorithms, particularly those related to automotive use cases (autonomous driving, vision, and LiDAR processing ML algorithms), is essential. Research experience in the development of efficient networks, various Neural Architecture Search (NAS) techniques, network quantization, and pruning is highly desirable. Strong communication and interpersonal skills are required, and the candidate must be able to work effectively with various horizontal AI teams. Minimum Qualifications: Bachelor's degree in Computer Science, Engineering, Information Systems, or related field and 1+ years of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR Master's degree in Computer Science, Engineering, Information Systems, or related field and 1+ year of Hardware Engineering, Software Engineering, Systems Engineering, or related work experience. OR PhD in Computer Science, Engineering, Information Systems, or related field. Preferred Qualifications: Good at software development with excellent analytical, development, and problem-solving skills. Strong understanding of Machine Learning fundamentals Hands-on experience with deep learning network design and implementation. Ability to define network from scratch in PyTorch, ability to add new loss function, modify network with torch.fx. Adept at version control system like GIT. Experience in neural network quantization, compression, pruning algorithms. Experience in deep learning kernel/compiler optimization Strong communication skills Principal Duties And Responsibilities: Applies Machine Learning knowledge to extend training or runtime frameworks or model efficiency software tools with new features and optimizations. Models, architects, and develops machine learning hardware (co-designed with machine learning software) for inference or training solutions. Develops optimized software to enable AI models deployed on hardware (e.g., machine learning kernels, compiler tools, or model efficiency tools, etc.) to allow specific hardware features; collaborates with team members for joint design and development. Assists with the development and application of machine learning techniques into products and/or AI solutions to enable customers to do the same. Develops, adapts, or prototypes complex machine learning algorithms, models, or frameworks aligned with and motivated by product proposals or roadmaps with minimal guidance from more experienced engineers. Conducts complex experiments to train and evaluate machine learning models and/or software independently. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail myhr.support@qualcomm.com or call Qualcomm's toll-free number found here . Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. Minimum Qualifications: Bachelor's degree in Engineering, Information Systems, Computer Science, or related field. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers. 3074561 Show more Show less

Company Qualcomm India Private Limited Job Area Engineering Group, Engineering Group > Software Engineering General Summary Job Description Join the exciting Generative AI team at Qualcomm focused on integrating cutting edge GenAI models on Qualcomm chipsets. The team uses Qualcomm chips’ extensive heterogeneous computing capabilities to allow inference of GenAI models on-device without a need for connection to the cloud. Our inference engine is designed to help developers run neural network models trained in a variety of frameworks on Snapdragon platforms at blazing speeds while still sipping the smallest amount of power. Utilize this power efficient hardware and Software stack to run Large Language Models (LLMs) and Large Vision Models (LVM) at near GPU speeds! Responsibilities In this role, you will spearhead the development and commercialization of the Qualcomm AI Runtime (QAIRT) SDK on Qualcomm SoCs. As an AI inferencing expert, you'll push the limits of performance from large models. Your mastery in deploying large C/C++ software stacks using best practices will be essential. You'll stay on the cutting edge of GenAI advancements, understanding LLMs/Transformers and the nuances of edge-based GenAI deployment. Most importantly, your passion for the role of edge in AI's evolution will be your driving force. Requirements Master’s/Bachelor’s degree in computer science or equivalent. 2-4 years of relevant work experience in software development. Strong understanding of Generative AI models – LLM, LVM, LMMs and building blocks (self-attention, cross attention, kv caching etc.) Floating-point, Fixed-point representations and Quantization concepts. Experience with optimizing algorithms for AI hardware accelerators (like CPU/GPU/NPU). Strong in C/C++ programming, Design Patterns and OS concepts. Good scripting skills in Python. Excellent analytical and debugging skills. Good communication skills (verbal, presentation, written). Ability to collaborate across a globally diverse team and multiple interests. Preferred Qualifications Strong understanding of SIMD processor architecture and system design. Proficiency in object-oriented software development and familiarity Familiarity with Linux and Windows environment Strong background in kernel development for SIMD architectures. Familiarity with frameworks like llama.cpp, MLX, and MLC is a plus. Good knowledge of PyTorch, TFLite, and ONNX Runtime is preferred. Experience with parallel computing systems and languages like OpenCL and CUDA is a plus. Minimum Qualifications Bachelor's degree in Engineering, Information Systems, Computer Science, or related field and 2+ years of Software Engineering or related work experience. OR Master's degree in Engineering, Information Systems, Computer Science, or related field and 1+ year of Software Engineering or related work experience. OR PhD in Engineering, Information Systems, Computer Science, or related field. 2+ years of academic or work experience with Programming Language such as C, C++, Java, Python, etc. Applicants : Qualcomm is an equal opportunity employer. If you are an individual with a disability and need an accommodation during the application/hiring process, rest assured that Qualcomm is committed to providing an accessible process. You may e-mail disability-accomodations@qualcomm.com or call Qualcomm's toll-free number found here. Upon request, Qualcomm will provide reasonable accommodations to support individuals with disabilities to be able participate in the hiring process. Qualcomm is also committed to making our workplace accessible for individuals with disabilities. (Keep in mind that this email address is used to provide reasonable accommodations for individuals with disabilities. We will not respond here to requests for updates on applications or resume inquiries). Qualcomm expects its employees to abide by all applicable policies and procedures, including but not limited to security and other requirements regarding protection of Company confidential information and other confidential and/or proprietary information, to the extent those requirements are permissible under applicable law. To all Staffing and Recruiting Agencies : Our Careers Site is only for individuals seeking a job at Qualcomm. Staffing and recruiting agencies and individuals being represented by an agency are not authorized to use this site or to submit profiles, applications or resumes, and any such submissions will be considered unsolicited. Qualcomm does not accept unsolicited resumes or applications from agencies. Please do not forward resumes to our jobs alias, Qualcomm employees or any other company location. Qualcomm is not responsible for any fees related to unsolicited resumes/applications. If you would like more information about this role, please contact Qualcomm Careers. 3075196 Show more Show less

Technical Expertise : (minimum 2 year relevant experience) ● Solid understanding of Generative AI models and Natural Language Processing (NLP) techniques, including Retrieval-Augmented Generation (RAG) systems, text generation, and embedding models. ● Exposure to Agentic AI concepts, multi-agent systems, and agent development using open-source frameworks like LangGraph and LangChain. ● Hands-on experience with modality-specific encoder models (text, image, audio) for multi-modal AI applications. ● Proficient in model fine-tuning, prompt engineering, using both open-source and proprietary LLMs. ● Experience with model quantization, optimization, and conversion techniques (FP32 to INT8, ONNX, TorchScript) for efficient deployment, including edge devices. ● Deep understanding of inference pipelines, batch processing, and real-time AI deployment on both CPU and GPU. ● Strong MLOps knowledge with experience in version control, reproducible pipelines, continuous training, and model monitoring using tools like MLflow, DVC, and Kubeflow. ● Practical experience with scikit-learn, TensorFlow, and PyTorch for experimentation and production-ready AI solutions. ● Familiarity with data preprocessing, standardization, and knowledge graphs (nice to have). ● Strong analytical mindset with a passion for building robust, scalable AI solutions. ● Skilled in Python, writing clean, modular, and efficient code. ● Proficient in RESTful API development using Flask, FastAPI, etc., with integrated AI/ML inference logic. ● Experience with MySQL, MongoDB, and vector databases like FAISS, Pinecone, or Weaviate for semantic search. ● Exposure to Neo4j and graph databases for relationship-driven insights. ● Hands-on with Docker and containerization to build scalable, reproducible, and portable AI services. ● Up-to-date with the latest in GenAI, LLMs, Agentic AI, and deployment strategies. ● Strong communication and collaboration skills, able to contribute in cross-functional and fast-paced environments. Bonus Skills ● Experience with cloud deployments on AWS, GCP, or Azure, including model deployment and model inferencing. ● Working knowledge of Computer Vision and real-time analytics using OpenCV, YOLO, and similar Show more Show less

Job Title: AI Engineer Want to join a startup, but with the stability of a larger organization? Join our innovation team at HGS that's focused on building SaaS products. If you are highly driven & passionate person who'd like to build highly scalable SaaS products in a startup type of environment, you're welcome to apply. The HGS Digital Innovation Team is designed to create products and solutions relevant for enterprises, discover innovations and to contextualize and experiment with them within a specific industry. This unit provides an environment for the exploration, development, and testing of Cloud-based Digital AI solutions. In addition to that it also looks at rapid deployment at scale and sustainability of these solutions for target business impacts. Job Overview We are seeking an agile AI Engineer with a strong focus on both AI engineering and SaaS product development in a 0-1 product environment. This role is perfect for a candidate skilled in building and iterating quickly, embracing a fail fast approach to bring innovative AI solutions to market rapidly. You will be responsible for designing, developing, and deploying SaaS products using advanced Large Language Models (LLMs) such as Meta, Azure OpenAI, Claude, and Mistral, while ensuring secure, scalable, and high-performance architecture. Your ability to adapt, iterate, and deliver in fast-paced environments is critical. Responsibilities Lead the design, development, and deployment of SaaS products leveraging LLMs, including platforms like Meta, Azure OpenAI, Claude, and Mistral. Support product lifecycle, from conceptualization to deployment, ensuring seamless integration of AI models with business requirements and user needs. Build secure, scalable, and efficient SaaS products that embody robust data management and comply with security and governance standards. Collaborate closely with product management, and other stakeholders to align AI-driven SaaS solutions with business strategies and customer expectations. Fine-tune AI models using custom instructions to tailor them to specific use cases and optimize performance through techniques like quantization and model tuning. Architect AI deployment strategies using cloud-agnostic platforms (AWS, Azure, Google Cloud), ensuring cost optimization while maintaining performance and scalability. Apply retrieval-augmented generation (RAG) techniques to build AI models that provide contextually accurate and relevant outputs. Build the integration of APIs and third-party services into the SaaS ecosystem, ensuring robust and flexible product architecture. Monitor product performance post-launch, iterating and improving models and infrastructure to enhance user experience and scalability. Stay current with AI advancements, SaaS development trends, and cloud technology to apply innovative solutions in product development. Qualifications Bachelor’s degree or equivalent in Information Systems, Computer Science, or related fields. 6+ years of experience in product development, with at least 2 years focused on AI-based SaaS products. Demonstrated experience in leading the development of SaaS products, from ideation to deployment, with a focus on AI-driven features. Hands-on experience with LLMs (Meta, Azure OpenAI, Claude, Mistral) and SaaS platforms. Proven ability to build secure, scalable, and compliant SaaS solutions, integrating AI with cloud-based services (AWS, Azure, Google Cloud). Strong experience with RAG model techniques and fine-tuning AI models for business-specific needs. Proficiency in AI engineering, including machine learning algorithms, deep learning architectures (e.g., CNNs, RNNs, Transformers), and integrating models into SaaS environments. Solid understanding of SaaS product lifecycle management, including customer-focused design, product-market fit, and post-launch optimization. Excellent communication and collaboration skills, with the ability to work cross-functionally and drive SaaS product success. Knowledge of cost-optimized AI deployment and cloud infrastructure, focusing on scalability and performance. Show more Show less