177 Onnx Jobs

Job Area: Engineering Group, Engineering Group > Software Engineering General Summary: 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. 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.

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

Job Summary We’re seeking a hands-on GenAI & Computer Vision Engineer with 3–5 years of experience delivering production-grade AI solutions. You must be fluent in the core libraries, tools, and cloud services listed below, and able to own end-to-end model development—from research and fine-tuning through deployment, monitoring, and iteration. In this role, you’ll tackle domain-specific challenges like LLM hallucinations, vector search scalability, real-time inference constraints, and concept drift in vision models. Key Responsibilities Generative AI & LLM Engineering Fine-tune and evaluate LLMs (Hugging Face Transformers, Ollama, LLaMA) for specialized tasks Deploy high-throughput inference pipelines using vLLM or Triton Inference Server Design agent-based workflows with LangChain or LangGraph, integrating vector databases (Pinecone, Weaviate) for retrieval-augmented generation Build scalable inference APIs with FastAPI or Flask, managing batching, concurrency, and rate-limiting Computer Vision Development Develop and optimize CV models (YOLOv8, Mask R-CNN, ResNet, EfficientNet, ByteTrack) for detection, segmentation, classification, and tracking Implement real-time pipelines using NVIDIA DeepStream or OpenCV (cv2); optimize with TensorRT or ONNX Runtime for edge and cloud deployments Handle data challenges—augmentation, domain adaptation, semi-supervised learning—and mitigate model drift in production MLOps & Deployment Containerize models and services with Docker; orchestrate with Kubernetes (KServe) or AWS SageMaker Pipelines Implement CI/CD for model/version management (MLflow, DVC), automated testing, and performance monitoring (Prometheus + Grafana) Manage scalability and cost by leveraging cloud autoscaling on AWS (EC2/EKS), GCP (Vertex AI), or Azure ML (AKS) Cross-Functional Collaboration Define SLAs for latency, accuracy, and throughput alongside product and DevOps teams Evangelize best practices in prompt engineering, model governance, data privacy, and interpretability Mentor junior engineers on reproducible research, code reviews, and end-to-end AI delivery Required Qualifications You must be proficient in at least one tool from each category below: LLM Frameworks & Tooling: Hugging Face Transformers, Ollama, vLLM, or LLaMA Agent & Retrieval Tools: LangChain or LangGraph; RAG with Pinecone, Weaviate, or Milvus Inference Serving: Triton Inference Server; FastAPI or Flask Computer Vision Frameworks & Libraries: PyTorch or TensorFlow; OpenCV (cv2) or NVIDIA DeepStream Model Optimization: TensorRT; ONNX Runtime; Torch-TensorRT MLOps & Versioning: Docker and Kubernetes (KServe, SageMaker); MLflow or DVC Monitoring & Observability: Prometheus; Grafana Cloud Platforms: AWS (SageMaker, EC2/EKS) or GCP (Vertex AI, AI Platform) or Azure ML (AKS, ML Studio) Programming Languages: Python (required); C++ or Go (preferred) Additionally: Bachelor’s or Master’s in Computer Science, Electrical Engineering, AI/ML, or a related field 3–5 years of professional experience shipping both generative and vision-based AI models in production Strong problem-solving mindset; ability to debug issues like LLM drift, vector index staleness, and model degradation Excellent verbal and written communication skills Typical Domain Challenges You’ll Solve LLM Hallucination & Safety: Implement grounding, filtering, and classifier layers to reduce false or unsafe outputs Vector DB Scaling: Maintain low-latency, high-throughput similarity search as embeddings grow to millions Inference Latency: Balance batch sizing and concurrency to meet real-time SLAs on cloud and edge hardware Concept & Data Drift: Automate drift detection and retraining triggers in vision and language pipelines Multi-Modal Coordination: Seamlessly orchestrate data flow between vision models and LLM agents in complex workflows About Company Hi there! We are Auriga IT. We power businesses across the globe through digital experiences, data and insights. From the apps we design to the platforms we engineer, we're driven by an ambition to create world-class digital solutions and make an impact. Our team has been part of building the solutions for the likes of Zomato, Yes Bank, Tata Motors, Amazon, Snapdeal, Ola, Practo, Vodafone, Meesho, Volkswagen, Droom and many more. We are a group of people who just could not leave our college-life behind and the inception of Auriga was solely based on a desire to keep working together with friends and enjoying the extended college life. Who Has not Dreamt of Working with Friends for a Lifetime Come Join In https://www.aurigait.com/ -https://aurigait.com/https://aurigait.com

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

Hello, Truecaller is calling you from Bangalore, India! Ready to pick up? Our goal is to make communication smarter, safer, and more efficient, all while building trust everywhere. We're all about bringing you smart services with a big social impact, keeping you safe from fraud, harassment, scam calls or messages, so you can focus on the conversations that matter. Top 20 most downloaded apps globally, and world’s #1 caller ID and spam-blocking service for Android and iOS, with extensive AI capabilities, with more than 400 million active users per month. Founded in 2009, listed on Nasdaq OMX Stockholm and is categorized as a Large Cap. Our focus on innovation, operational excellence, sustainable growth, and collaboration has resulted in consistently high profitability and strong EBITDA margins. A team of 400 people from ~35 different nationalities spread across our headquarters in Stockholm and offices in Bangalore, Mumbai, Gurgaon and Tel Aviv with high ambitions. We in the Insights Team are responsible for SMS Categorization, Fraud detection and other Smart SMS features within the Truecaller app. The OTP & bank notifications, bill & travel reminder alerts are some examples of the Smart SMS features. The team has developed a patented offline text parser that powers all these features and the team is also exploring cutting edge technologies like LLM to enhance the Smart SMS features. The team’s mission is to become the World’s most loved and trusted SMS app which is aligned with Truecaller’s vision to make communication safe and efficient. Smart SMS is used by over 90M users every day. As an ML Engineer , you will be responsible for collecting, organizing, analyzing, and interpreting Truecaller data with a focus on NLP. In this role, you will be working hands-on to optimize the training and deployment of ML models to be quick and cost-efficient. Also, you will be pivotal in advancing our work with large language models and in-device models across diverse regions. Your expertise will enhance our natural language processing, machine learning, and predictive analytics capabilities. What you bring in : 3+ years in machine learning engineering, with hands-on involvement in feature engineering, model development, and deployment. Experience in Natural Language Processing (NLP), with a deep understanding of text processing, model development, and deployment challenges in the domain. Proven ability to develop, deploy, and maintain machine learning models in production environments, ensuring scalability, reliability, and performance. Strong familiarity with ML frameworks like TensorFlow, PyTorch, and ONNX, and experience in tech stack such as Kubernetes, Docker, APIs, Vertex AI, GCP. Experience deploying models across backend and mobile platforms. Fine-tune and optimize LLMs prompts for domain-specific applications Ability to optimize feature engineering, model training, and deployment strategies for performance and efficiency. Strong SQL and statistical skills. Programming knowledge in at least one language, such as Python or R. Preferably python. Knowledge of machine learning algorithms. Excellent teamwork and communication skills, with the ability to work cross-functionally with product, engineering, and data science teams. Good to have the knowledge in retrieval-based pipelines to enhance LLM performance The impact you will create: Collaborate with Product and Engineering to scope, design, and implement systems that solve complex business problems ensuring they are delivered on time and within scope. Design, develop, and deploy state-of-the-art NLP models, contributing directly to message classification and fraud detection at scale for millions of users. Leverage cutting-edge NLP techniques to enhance message understanding, spam filtering, and fraud detection, ensuring a safer and more efficient messaging experience. Build and optimize ML models that can efficiently handle large-scale data processing while maintaining accuracy and performance. Work closely with data scientists and data engineers to enable rapid experimentation, development, and productionization of models in a cost-effective manner. Streamline the ML lifecycle, from training to deployment, by implementing automated workflows, CI/CD pipelines, and monitoring tools for model health and performance. Stay ahead of advancements in ML and NLP, proactively identifying opportunities to enhance model performance, reduce latency, and improve user experience. Your work will directly impact millions of users, improving message classification, fraud detection, and the overall security of messaging platforms. It would be great if you also have: Understanding of Conversational AI Deploying NLP models in production Working knowledge of GCP components Cloud-based LLM inference with Ray, Kubernetes, and serverless architectures. Life at Truecaller - Behind the code: https://www.instagram.com/lifeattruecaller/ Sounds like your dream job? We will fill the position as soon as we find the right candidate, so please send your application as soon as possible. As part of the recruitment process, we will conduct a background check. This position is based in Bangalore , India. We only accept applications in English. What we offer: A smart, talented and agile team: An international team where ~35 nationalities are working together in several locations and time zones with a learning, sharing and fun environment. A great compensation package: Competitive salary, 30 days of paid vacation, flexible working hours, private health insurance, parental leave, telephone bill reimbursement, Udemy membership to keep learning and improving and Wellness allowance. Great tech tools: Pick the computer and phone that you fancy the most within our budget ranges. Office life: We strongly believe in the in-person collaboration and follow an office-first approach while offering some flexibility. Enjoy your days with great colleagues with loads of good stuff to learn from, daily lunch and breakfast and a wide range of healthy snacks and beverages. In addition, every now and then check out the playroom for a fun break or join our exciting parties and or team activities such as Lab days, sports meetups etc. There something for everyone! Come as you are: Truecaller is diverse, equal and inclusive. We need a wide variety of backgrounds, perspectives, beliefs and experiences in order to keep building our great products. No matter where you are based, which language you speak, your accent, race, religion, color, nationality, gender, sexual orientation, age, marital status, etc. All those things make you who you are, and that’s why we would love to meet you.

Role Overview We're looking for a Python-based AI/ML Developer who brings solid hands-on experience in building machine learning models and deploying them into scalable, production-ready APIs using FastAPI or Django. The ideal candidate is both analytical and implementation-savvy, capable of transforming models into live services and integrating them with real-world systems. Key Responsibilities Design, train, and evaluate machine learning models (classification, regression, clustering, etc.) Build and deploy scalable REST APIs for model serving using FastAPI or Django Collaborate with data scientists, backend developers, and DevOps to integrate models into production systems Develop clean, modular, and optimized Python code using best practices Perform data preprocessing, feature engineering, and data visualization using Pandas, NumPy, Matplotlib, and Seaborn Implement model serialization techniques (Pickle, Joblib, ONNX) and deploy models using containers (Docker) Manage API security with JWT and OAuth mechanisms Participate in Agile development with code reviews, Git workflows, CI/CD pipelines Must-Have Skills Python & Development : Proficient in Python 3.x, OOP, and clean code principles Experience with Git, Docker, debugging, unit testing AI/ML Good grasp of supervised/unsupervised learning, model evaluation, and data wrangling Hands-on with Scikit-learn, XGBoost, LightGBM Web Frameworks FastAPI : API routes, async programming, Pydantic, JWT Django : REST Framework, ORM, Admin panel, Middleware DevOps & Cloud Experience with containerized deployment using Docker Exposure to cloud platforms: AWS, Azure, or GCP CI/CD with GitHub Actions, Jenkins, or GitLab CI Databases SQL : PostgreSQL, MySQL NoSQL : MongoDB, Redis ORM : Django ORM, Skills : Model tracking/versioning tools (MLflow, DVC) Knowledge of LLMs, transformers, vector DBs (Pinecone, Faiss) Airflow, Prefect, or other workflow automation tools Basic frontend skills (HTML, JavaScript, React) Requirements Education: B.E./B.Tech or M.E./M.Tech in Computer Science, Data Science, or related fields Experience: 3-6 years of industry experience in ML development and backend API integration Strong communication skills and ability to work with cross-functional teams (ref:hirist.tech)

Job Description 💰 Compensation Note: The budget for this role is fixed at INR 50–55 lakhs per annum (non-negotiable). Please ensure this aligns with your expectations before applying. 📍 Work Setup: This is a hybrid role , requiring 3 days per week onsite at the office in Hyderabad, India . 📝 Interview Process: The process consists of 6 stages , including a technical assessment, code review, code discussion , and panel interviews . Company Description: Blend is a premier AI services provider, committed to co-creating meaningful impact for its clients through the power of data science, AI, technology, and people. With a mission to fuel bold visions, Blend tackles significant challenges by seamlessly aligning human expertise with artificial intelligence. The company is dedicated to unlocking value and fostering innovation for its clients by harnessing world-class people and data-driven strategy. We believe that the power of people and AI can have a meaningful impact on your world, creating more fulfilling work and projects for our people and clients. Job Description : We are looking for an AI Engineer with experience in Speech-to-text and Text Generation to solve a Conversational AI challenge for our client based in EMEA. The focus of this project is to transcribe conversations and leverage generative AI-powered text analytics to drive better engagement strategies and decision-making. The ideal candidate will have deep expertise in Speech-to-Text (STT), Natural Language Processing (NLP), Large Language Models (LLMs), and Conversational AI systems. This role involves working on real-time transcription, intent analysis, sentiment analysis, summarization, and decision-support tools. Key Responsibilities: Conversational AI & Call Transcription Development Develop and fine-tune automatic speech recognition (ASR) models Implement language model fine-tuning for industry-specific language. Develop speaker diarization techniques to distinguish speakers in multi-speaker conversations. NLP & Generative AI Applications Build summarization models to extract key insights from conversations. Implement Named Entity Recognition (NER) to identify key topics. Apply LLMs for conversation analytics and context-aware recommendations. Design custom RAG (Retrieval-Augmented Generation) pipelines to enrich call summaries with external knowledge. Sentiment Analysis & Decision Support Develop sentiment and intent classification models. Create predictive models that suggest next-best actions based on call content, engagement levels, and historical data. AI Deployment & Scalability Deploy AI models using tools like AWS, GCP, Azure AI, ensuring scalability and real-time processing. Optimize inference pipelines using ONNX, TensorRT, or Triton for cost-effective model serving. Implement MLOps workflows to continuously improve model performance with new call data. Qualifications: Technical Skills Strong experience in Speech-to-Text (ASR), NLP, and Conversational AI. Hands-on expertise with tools like Whisper, DeepSpeech, Kaldi, AWS Transcribe, Google Speech-to-Text. Proficiency in Python, PyTorch, TensorFlow, Hugging Face Transformers. Experience with LLM fine-tuning, RAG-based architectures, and LangChain. Hands-on experience with Vector Databases (FAISS, Pinecone, Weaviate, ChromaDB) for knowledge retrieval. Experience deploying AI models using Docker, Kubernetes, FastAPI, Flask. Soft Skills Ability to translate AI insights into business impact. Strong problem-solving skills and ability to work in a fast-paced AI-first environment. Excellent communication skills to collaborate with cross-functional teams, including data scientists, engineers, and client stakeholders. Preferred Qualifications Experience in healthcare, pharma, or life sciences NLP use cases. Background in knowledge graphs, prompt engineering, and multimodal AI. Experience with Reinforcement Learning (RLHF) for improving conversation models.

Company Description At Nielsen, we are passionate about our work to power a better media future for all people by providing powerful insights that drive client decisions and deliver extraordinary results. Our talented, global workforce is dedicated to capturing audience engagement with content - wherever and whenever it’s consumed. Together, we are proudly rooted in our deep legacy as we stand at the forefront of the media revolution. When you join Nielsen, you will join a dynamic team committed to excellence, perseverance, and the ambition to make an impact together. We champion you, because when you succeed, we do too. We enable your best to power our future. Job Description Responsibilities: Research, design, develop, implement and test econometric, statistical, optimization and machine learning models. Design, write and test modules for Nielsen analytics platforms using Python, R, SQL and/or Spark. Utilize advanced computational/statistics libraries including Spark MLlib, Scikit-learn, SciPy, StatsModels. Collaborate with cross functional Data Science, Product, and Technology teams to integrate best practices from across the organization Provide leadership and guidance for the team in the of adoption of new tools and technologies to improve our core capabilities Execute and refine the roadmap to upgrade the modeling/forecasting/control functions of the team to improve upon the core service KPI’s Ensure product quality, stability, and scalability by facilitating code reviews and driving best practices like modular code, unit tests, and incorporating CI/CD workflows Explain complex data science (e.g. model-related) concepts in simple terms to non-technical internal and external audiences Qualifications Key Skills: 5+ years of professional work experience in Statistics, Data Science, and/or related disciplines, with focus on delivering analytics software solutions in a production environment Strong programming skills in Python with experience in NumPy, Pandas, SciPy and Scikit-learn. Hands-on experience with deep learning frameworks (PyTorch, TensorFlow, Keras). Solid understanding of Machine learning domains such as Computer Vision, Natural Language Processing and classical Machine Learning. Proficiency in SQL and NoSQL databases for large-scale data manipulation Experience with cloud-based ML services (AWS SageMaker, Databricks, GCP AI, Azure ML). Knowledge of model deployment (FastAPI, Flask, TensorRT, ONNX) MLOps tools (MLflow, Kubeflow, Airflow) and containerization. Preferred skills: Understanding of LLM fine-tuning, tokenization, embeddings, and multimodal learning. Familiarity with vector databases (FAISS, Pinecone) and retrieval-augmented generation (RAG). Familiarity with advertising intelligence, recommender systems, and ranking models. Knowledge of CI/CD for ML workflows, and software development best practices. Additional Information Please be aware that job-seekers may be at risk of targeting by scammers seeking personal data or money. Nielsen recruiters will only contact you through official job boards, LinkedIn, or email with a nielsen.com domain. Be cautious of any outreach claiming to be from Nielsen via other messaging platforms or personal email addresses. Always verify that email communications come from an @nielsen.com address. If you're unsure about the authenticity of a job offer or communication, please contact Nielsen directly through our official website or verified social media channels.

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

Overview Working at Atlassian Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Interviews and onboarding are conducted virtually, a part of being a distributed-first company. Responsibilities As a Machine Learning engineer, you will independently work on the development and implementation of the cutting edge machine learning algorithms, training sophisticated models, collaborating with engineering and analytics teams, to build the AI functionality for Atlassian. Your daily responsibilities will encompass a broad spectrum of tasks such as understanding system and model architectures, conducting rigorous experimentation and model evaluations and dealing with related problems. Your role is pivotal, stretching beyond these tasks, ensuring AI's transformative potential is realized across Atlassian products and platforms. What You’ll Do As an associate Machine Learning engineer, you will work on the development and implementation of the cutting edge machine learning algorithms, training sophisticated models, collaborating with engineering and analytics teams, to build the AI functionality into various tools/platform. Your daily responsibilities will encompass a broad spectrum of tasks such as designing system and model architectures, conducting rigorous experimentation and model evaluations. Qualifications On the first day, we'll expect you to have Bachelor's or Master's degree (preferably a Computer Science degree or equivalent experience). 2+ years of related industry experience in the data science domain. Familiarity in Python/Java/Golang/Typescript with and the ability to write performant production-quality code, familiarity with SQL, knowledge of Spark and cloud data environments (e.g. AWS, GCloud, Databricks). Familiarity with LLMs (prompt engineering, RAG), AirFlow, MLFlow, model inferencing, ONNX pipelines will be preferred. Great verbal and written communication skills along with the ability to explain complex data science and ML concepts to diverse audiences. Ability to craft compelling stories with data. Focus on business practicality and the 80/20 rule; very high bar for output quality, but recognize the business benefit of "having something now" vs "perfection sometime in the future". Agile development mindset, appreciating the benefit of constant iteration and improvement. Preference for folks who have worked prior in remote and/or hybrid environments. Our Perks & Benefits Atlassian offers a variety of perks and benefits to support you, your family and to help you engage with your local community. Our offerings include health coverage, paid volunteer days, wellness resources, and so much more. Visit go.atlassian.com/perksandbenefits to learn more. About Atlassian At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together. We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines. To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them. To learn more about our culture and hiring process, visit go.atlassian.com/crh .

Overview Working at Atlassian Atlassians can choose where they work – whether in an office, from home, or a combination of the two. That way, Atlassians have more control over supporting their family, personal goals, and other priorities. We can hire people in any country where we have a legal entity. Interviews and onboarding are conducted virtually, a part of being a distributed-first company. Your future team Transformations AI foundations is a core pillar inside the DevInfra org. Its purpose is to build AI-powered developer productivity tools for internal and external customers. Responsibilities As a Machine Learning engineer, you will independently work on the development and implementation of the cutting edge machine learning algorithms, training sophisticated models, collaborating with engineering and analytics teams, to build the AI functionality for Atlassian. Your daily responsibilities will encompass a broad spectrum of tasks such as understanding system and model architectures, conducting rigorous experimentation and model evaluations and dealing with related problems. Your role is pivotal, stretching beyond these tasks, ensuring AI's transformative potential is realized across Atlassian products and platforms. What You’ll Do As an associate Machine Learning engineer, you will work on the development and implementation of the cutting edge machine learning algorithms, training sophisticated models, collaborating with engineering and analytics teams, to build the AI functionality into various tools/platform. Your daily responsibilities will encompass a broad spectrum of tasks such as designing system and model architectures, conducting rigorous experimentation and model evaluations. Qualifications On the first day, we'll expect you to have Bachelor's or Master's degree (preferably a Computer Science degree or equivalent experience). 2+ years of related industry experience in the data science domain. Familiarity in Python/Java/Golang/Typescript with and the ability to write performant production-quality code, familiarity with SQL, knowledge of Spark and cloud data environments (e.g. AWS, GCloud, Databricks). Familiarity with LLMs (prompt engineering, RAG), AirFlow, MLFlow, model inferencing, ONNX pipelines will be preferred. Great verbal and written communication skills along with the ability to explain complex data science and ML concepts to diverse audiences. Ability to craft compelling stories with data. Focus on business practicality and the 80/20 rule; very high bar for output quality, but recognize the business benefit of "having something now" vs "perfection sometime in the future". Agile development mindset, appreciating the benefit of constant iteration and improvement. Preference for folks who have worked prior in remote and/or hybrid environments. Our Perks & Benefits Atlassian offers a variety of perks and benefits to support you, your family and to help you engage with your local community. Our offerings include health coverage, paid volunteer days, wellness resources, and so much more. Visit go.atlassian.com/perksandbenefits to learn more. About Atlassian At Atlassian, we're motivated by a common goal: to unleash the potential of every team. Our software products help teams all over the planet and our solutions are designed for all types of work. Team collaboration through our tools makes what may be impossible alone, possible together. We believe that the unique contributions of all Atlassians create our success. To ensure that our products and culture continue to incorporate everyone's perspectives and experience, we never discriminate based on race, religion, national origin, gender identity or expression, sexual orientation, age, or marital, veteran, or disability status. All your information will be kept confidential according to EEO guidelines. To provide you the best experience, we can support with accommodations or adjustments at any stage of the recruitment process. Simply inform our Recruitment team during your conversation with them. To learn more about our culture and hiring process, visit go.atlassian.com/crh .

About the Role You’ll join a small, fast team turning cutting-edge AI research into shippable products across text, vision, and multimodal domains. One sprint you’ll be distilling an LLM for WhatsApp chat-ops; the next you’ll be converting CAD drawings to BOM stories, or training a computer-vision model that flags onsite safety risks. You own the model life-cycle end-to-end: data prep ➞ fine-tune/distil ➞ evaluate ➞ deploy ➞ monitor. Key Responsibilities Model Engineering • Fine-tune and quantise open-weight LLMs (Llama 3, Mistral, Gemma) and SLMs for low-latency edge inference. • Train or adapt computer-vision models (YOLO, Segment Anything, SAM-DINO) to detect site hazards, drawings anomalies, or asset states. Multimodal Pipelines • Build retrieval-augmented-generation (RAG) stacks: loaders → vector DB (FAISS / OpenSearch) → ranking prompts. • Combine vision + language outputs into single “scene → story” responses for dashboards and WhatsApp bots. Serving & MLOps • Package models as Docker images, SageMaker endpoints, or ONNX edge bundles; expose FastAPI/GRPC handlers with auth, rate-limit, telemetry. • Automate CI/CD: GitHub Actions → Terraform → blue-green deploys. Evaluation & Guardrails • Design automatic eval harnesses (BLEU, BERTScore, CLIP similarity, toxicity & bias checks). • Monitor drift, hallucination, latency; implement rollback triggers. Enablement & Storytelling • Write prompt playbooks & model cards so other teams can reuse your work. • Run internal workshops: “From design drawing to narrative” / “LLM safety by example”. Required Skills & Experience 3+ yrs ML/NLP/CV in production; at least 1 yr hands-on with Generative AI . Strong Python (FastAPI, Pydantic, asyncio) and HuggingFace Transformers OR diffusers . Experience with minima­l-footprint models (LoRA, QLoRA, GGUF, INT-4) and vector search. Comfortable on AWS/GCP/Azure for GPU instances, serverless endpoints, IaC. Solid grasp of evaluation/guardrail frameworks (Helm, PromptLayer, Guardrails-AI, Triton metrics). Bonus Points Built a RAG or function-calling agent used by 500+ users. Prior CV pipeline (object-detection, segmentation) or speech-to-text real-time project. Live examples of creative prompt engineering or story-generation. Familiarity with LangChain, LlamaIndex, or BentoML. Why You’ll Love It Multidomain playground – text, vision, storytelling, decision-support. Tech freedom – pick the right model & stack; justify it; ship it. Remote-first – work anywhere ±4 hrs of IST; quarterly hack-weeks in Hyderabad. Top-quartile pay – base + milestone bonus + conference stipend. How to Apply Send a resume and link to GitHub / HF / Kaggle showcasing LLM or CV work. Include a 200-word note describing your favourite prompt or model tweak and the impact it had. Short-listed candidates complete a practical take-home (fine-tune tiny model, build RAG or vision demo, brief write-up) and a 45-min technical chat. We hire builders, not resume keywords. Show us you can ship AI that works in the real world—and explain it clearly—and you’re in.

BeGig is the leading tech freelancing marketplace. We empower innovative, early-stage, non-tech founders to bring their visions to life by connecting them with top-tier freelance talent. By joining BeGig, you're not just taking on one role—you’re signing up for a platform that will continuously match you with high-impact opportunities tailored to your expertise.. Your Opportunit. yJoin our network as a Computer Vision Engineer and help startups build AI systems that understand, analyze, and act on visual data. From object detection and facial recognition to medical imaging and video analytics, you'll work on real-world use cases that require state-of-the-art computer vision solutions. . Role Overvi. ewAs a Computer Vision Engineer, you wil. l:Design, train, and deploy computer vision models for specific business applicatio. nsWork with image, video, or 3D data to extract insights and automate workflo. wsCollaborate with teams to integrate CV models into scalable produc. ts. What You’ll. DoBuild and fine-tune models for classification, detection, segmentation, tracking, or. OCRUse libraries like OpenCV, PyTorch, TensorFlow, Detectron2, or Y. OLOPreprocess and augment datasets to improve model robustn. essDeploy models using APIs, edge devices, or cloud-based inference to. olsMonitor performance and continuously optimize for accuracy and sp. eed. Technical Requirem. ents3+ years of experience in computer vision or deep lear. ningProficient in Python and frameworks like PyTorch, TensorFlow, or K. erasExperience with OpenCV, scikit-image, and image/video processing pipel. inesFamiliarity with model deployment using ONNX, TensorRT, or cloud serv. icesBonus: experience with real-time CV, synthetic data, or 3D vi. sion. What We’re Lookin. g ForA hands-on developer who can take vision-based problems from idea to produ. ctionA freelancer who enjoys working with data-rich products and diverse use. casesSomeone who can collaborate with both technical and product teams to deliver real i. mpact. Why J. oin UsWork on challenging computer vision projects across indu. striesFully remote and flexible freelance opportu. nitiesGet matched with future roles in CV, AI, and edge depl. oymentJoin a growing network solving real-world problems with intelligent vision s. ystems. Ready to bring vision to life? Apply now to become a Computer Vision Engineer with. BeGig.. Show more Show less

About Us:. We are an innovative company revolutionising retail checkout experiences by replacing traditional barcodes with cutting-edge Computer Vision technology. Our platform enables seamless, faster, and smarter checkout processes, enhancing the shopping experience for both retailers and consumers. We're growing rapidly and are looking for an experienced Android/Cross-Platform App Developer to join our team and help us build the future of retail technology.. Key Responsibilities:. Lead the research, design, and development of advanced computer vision models for tasks like object detection, tracking, segmentation, OCR, scene understanding, and 3D vision.. Translate business needs into scalable scientific solutions using state-of-the-art deep learning and classical computer vision techniques.. Design and implement experiments to evaluate performance, robustness, and accuracy of CV models in real-world production scenarios.. Collaborate with cross-functional teams including software engineering, product, and data teams to integrate vision models into applications. Drive innovation through internal IP generation (patents, publications) and contribute to the long-term AI/ML roadmap.. Provide scientific and technical leadership, mentoring junior scientists and reviewing designs and architectures.. Stay up to date with latest developments in AI, deep learning, and computer vision through academic and industrial research.e with industry best practices and emerging technologies to drive continuous improvement.. Qualifications:. S. 5+ years of hands-on experience in building and deploying production-grade computer vision models.. Strong theoretical background and applied experience in deep learning frameworks (e.g., PyTorch) and model architectures (e.g., CNNs, Vision Transformers, Diffusion Models).. Experience in working with large-scale datasets, training pipelines, and performance evaluation metrics.. Proficiency in Python and scientific computing libraries (e.g., NumPy, OpenCV, scikit-learn).. Experience with model optimization for edge deployment (ONNX, TensorRT, pruning/quantization) is a strong plus.. Strong written and verbal communication skills, with a track record of mentoring and collaboration.. Preferred Qualifications:. Experience with computer vision in real-time systems (e.g., AR/VR, robotics, automotive, surveillance).. Published research papers in top-tier conferences (CVPR, ICCV, NeurIPS, etc.).. Exposure to MLOps or ML model lifecycle in production environments.. Familiarity with cloud platforms (AWS/GCP/Azure) and containerization tools (Docker, Kubernetes) and basic bash scripting.. Show more Show less

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

A hands-on engineering position responsibe for designing, automating, and maintaining robust buid systems and depoyment pipeines for AI/ML components, with direct deveopment responsibiities in C++ and Python. The roe supports both mode training infrastructure and high-performance inference systems. Design and impement robustbuid automation systemsthat support arge, distributed AI/C++/Python codebases. Deveop toos and scripts that enabe deveopers and researchers to rapidy iterate, test, and depoy across diverse environments. Integrate C++ components with Python-based AI workfows, ensuring compatibiity, performance, and maintainabiity. Lead the creation ofportabe, reproducibe deveopment environments, ensuring parity between deveopment and production. Maintain and extend CI/CD pipeines for Linux and z/OS, impementing best practices in automated testing, artifact management, and reease vaidation. Coaborate with cross-functiona teams incuding AI researchers, system architects, and mainframe engineers to aign infrastructure with strategic goas. Proactivey monitor and improve buid performance, automation coverage, and system reiabiity. Contribute to interna documentation, process improvements, and knowedge sharing to scae your impact across teams. Required education Bacheor's Degree Preferred education Bacheor's Degree Required technica and professiona expertise Strong programming skis in C++ and Python, with a deep understanding of both compied and interpreted anguage paradigms. Hands-on experience buiding and maintainingcompex automation pipeines(CI/CD) using toos ikeJenkins, or GitLab CI. In-depth experience withbuid toos and systemssuch asCMake, Make, Meson, or Ninja, incuding custom script deveopment and cross-compiation. Experience working onmuti-patform deveopment, specificay onLinux and IBM z/OSenvironments, incuding understanding of their respective toochains and constraints. Experience integratingnative C++ code with Python, everagingpybind11,Cython, or simiar toos for high-performance interoperabiity. Proven abiity to troubeshoot and resovebuid-time, runtime, and integration issuesin arge-scae, muti-component systems. Comfortabe withshe scripting(Bash, Zsh, etc.) and system-eve operations. Famiiarity withcontainerization technoogiesike Docker for deveopment and depoyment environments. Preferred technica and professiona experience Working knowedge of AI/ML frameworks such as PyTorch, TensorFow, or ONNX, incuding understanding of how they integrate into production environments. Experience deveoping or maintaining software on IBM z/OS mainframe systems. Famiiarity with z/OS buid and packaging workfows, Understanding of system performance tuning, especiay in high-throughput compute or I/O environments (e.g., arge mode training or inference). Knowedge of GPU computing and ow-eve profiing/debugging toos. Experience managing ong-ifecyce enterprise systems and ensuring compatibiity across reeases and depoyments. Background contributing to or maintaining open-source projects in the infrastructure, DevOps, or AI tooing space Proficiency in distributed systems, microservice architecture, and REST APIs. Experience in coaborating with cross-functiona teams to integrate MLOps pipeines with CI/CD toos for continuous integration and depoyment, ensuring seamess integration of AI/ML modes into production workfows. Strong communication skis with the abiity to communicate technica concepts effectivey to non-technica stakehoders. Demonstrated exceence in interpersona skis, fostering coaboration across diverse teams. Proven track record of ensuring compiance with industry best practices and standards in AI engineering. Maintained high standards of code quaity, performance, and security in AI projects.

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.

About Balancehero India Balancehero India Pvt. Ltd. (BHI), the wholly-owned subsidiary of Balancehero Co. Ltd., Korea which runs and operates the mobile app “True Balance”- a one-stop destination for financial services.” Founded by Charlie Lee in Korea in 2014, Balancehero started its operations in India in the year 2016. It started off as a balance check application and the company has expanded its business model to financial services. The company aims to build a financial platform for the next billion which set the context for loans, utility services, pay later services, and commerce services. The Company's wholly-owned subsidiary True Credits Private Limited, is a licensed NBFC that aims to bridge the financial gap in India by making Finance available for all. True Credits lends through the True Balance mobile application. About True Balance Owned and operated by BalanceHero Group, True Balance is an RBI authorized Prepaid Payment Instrument (PPI) issuing entity. It offers loans through its subsidiary and RBI licensed Non-Banking Financial Company - True Credits Private Limited and other RBI licensed partners. Founded in 2016, as a mobile app for users in India to efficiently manage their phone calls and data usage, True Balance is now India’s one of the top financial services platforms providing solutions to all the financial needs of its users - from obtaining instant loans, paying utility bills to do prepaid recharges seamlessly. To date, True Balance has raised more than US$84 million in equity funding from marquee global investors like Softbank, Naver, and Line to name a few. The company aims to become the go-to financial services platform for the next billion people in India, playing a key role in the nationwide push towards the goal of Digital India and advancing financial inclusion amongst the unbanked and underbanked people. Balancehero India | LinkedIn About True Credits Established in 2019, True Credits is the RBI licensed NBFC that provides innovative financial services to empower the next billion unbanked users. They cater to the personal and business needs of consumers by providing fast and hassle-free finance. True Credits is focused towards unbanked users who have created a huge demand for instant credit services in India. Job Description: About the Role : BalanceHero's ML Engineer builds and operates training/serving systems and data pipelines for ML/LLM powered applications related to marketing/review/recovery of loan products. About the Responsibilities Building and operating data pipelines and feature stores for training and serving ML/LLM models Building and operating ML/LLM model serving systems Building and operating monitoring systems for ML/LLM powered applications Managing and deploying ML/LLM model versions Requirements Fluent in Python Experience on designing and building data pipelines for large-scale data using Hadoop Ecosystem in a cloud environment Experience on managing model versions and deployments while continuously updating one or more ML-powered applications Experience on operating ML Products that provide real-time prediction services Experience on open source (Triton, torchserve, BentoML, ONNX, etc.) and cloud solutions (AWS Sagemaker Endpoint, GCP Vertex AI, etc.) for model serving Experience on monitoring data shift and consistency while maintaining ML/LLM powered applications Preferred qualification Experience on Pyspark and Polars in large scale project Experience on AWS ML-related services (EMR, Glue, Sagemaker, Athena, etc.) Experience optimizing high-performance models using GPU Roles and responsibilities: About the Role: BalanceHero's ML Engineer builds and operates training/serving systems and data pipelines for ML/LLM powered applications related to marketing/review/recovery of loan products. About the Responsibilities Building and operating data pipelines and feature stores for training and serving ML/LLM models Building and operating ML/LLM model serving systems Building and operating monitoring systems for ML/LLM powered applications Managing and deploying ML/LLM model versions . Required Experience : Fluent in Python Experience on designing and building data pipelines for large-scale data using Hadoop Ecosystem in a cloud environment Experience on managing model versions and deployments while continuously updating one or more ML-powered applications Experience on operating ML Products that provide real-time prediction services Experience on open source (Triton, torchserve, BentoML, ONNX, etc.) and cloud solutions (AWS Sagemaker Endpoint, GCP Vertex AI, etc.) for model serving Experience on monitoring data shift and consistency while maintaining ML/LLM powered applications

Position: AI ML Engineer Job Description: 2 to 5+ years of experience in understanding the problem statement, data handling/triage, selecting and improving neural network models using deep learning frameworks to solve business problems. Excellent hands-on Coding in Python (mandatory), C/C++ or Java. Experience in developing AI/ML/DL models by using transfer learning or from scratch. Reasonably good knowledge on leading deep learning frameworks like Tensorflow, PyTorch, ONNX, Keras and others. Working experience in computer vision models like Yolo, Mobilenet, Resnet etc. Good understanding and working knowledge of AI/ML/DL on Edge (for e.g. Nvidia Jetson family, Qualcomm, Intel, Rpi). Thorough understanding and experience of DL/AI/ML lifecycle - full neural network pipeline, starting from data collection to model building to experimental framework to data analytics. Developed/optimized various models in computing domain (Video, Statistics , Audio and others). Demonstrated experience in completing data science projects with or without minimal supervision. Must possess conceptual understanding of various modelling techniques, pros and cons of each technique. Added Advantage: Proven record of migrating Al/ML/DL models/algorithms to low level platforms. Familiar with optimizing code for minimal usage of CPU and memory. Location: IN-GJ-Ahmedabad, India-Ognaj (eInfochips) Time Type: Full time Job Category: Engineering Services

Total yrs of exp: 7+ yrs Balewadi,Pune Location Immediate to 30 Days only Responsibilities - Overall 6+ years of experience, out of which in 5+ in AI, ML and Gen AI and related technologies Proven track record of leading and scaling AI/ML teams and initiatives Strong understanding and hands-on experience in AI, ML, Deep Learning, and Generative AI concepts and applications Expertise in ML frameworks such as PyTorch and/or TensorFlow Experience with ONNX runtime, model optimization and hyperparameter tuning Solid Experience of DevOps, SDLC, CI/CD, and MLOps practices - DevOps/MLOps Tech Stack: Docker, Kubernetes, Jenkins, Git, CI/CD, RabbitMQ, Kafka, Spark, Terraform, Ansible, Prometheus, Grafana, ELK stack Experience in production-level deployment of AI models at enterprise scale Proficiency in data preprocessing, feature engineering, and large-scale data handling Expertise in image and video processing, object detection, image segmentation, and related CV tasks Proficiency in text analysis, sentiment analysis, language modeling, and other NLP applications Experience with speech recognition, audio classification, and general signal processing techniques Experience with RAG, VectorDB, GraphDB and Knowledge Graphs Extensive experience with major cloud platforms (AWS, Azure, GCP) for AI/ML deployments. Proficiency in using and integrating cloud-based AI services and tools (e.g., AWS SageMaker, Azure ML, Google Cloud AI) Qualifications - [Education details] Required Skills Strong leadership and team management skills Excellent verbal and written communication skills Strategic thinking and problem-solving abilities Adaptability and adapting to the rapidly evolving AI/ML landscape Strong collaboration and interpersonal skills Ability to translate market needs into technological solutions Strong understanding of industry dynamics and ability to translate market needs into technological solutions Demonstrated ability to foster a culture of innovation and creative problem-solving Preferred Skills Pay range and compensation package - [Pay range or salary or compensation] Equal Opportunity Statement - [Include a statement on commitment to diversity and inclusivity.] Show more Show less

Responsibilities: Overall 4+ years of experience, out of which in 3+ in AI, ML and Gen AI and related technologies Proven track record of leading and scaling AI/ML teams and initiatives. Strong understanding and hands-on experience in AI, ML, Deep Learning, and Generative AI concepts and applications. Expertise in ML frameworks such as PyTorch and/or TensorFlow Experience with ONNX runtime, model optimization and hyperparameter tuning. Solid Experience of DevOps, SDLC, CI/CD, and MLOps practices - DevOps/MLOps Tech Stack: Docker, Kubernetes, Jenkins, Git, CI/CD, RabbitMQ, Kafka, Spark, Terraform, Ansible, Prometheus, Grafana, ELK stack Experience in production-level deployment of AI models at enterprise scale. Proficiency in data preprocessing, feature engineering, and large-scale data handling. Expertise in image and video processing, object detection, image segmentation, and related CV tasks. Proficiency in text analysis, sentiment analysis, language modeling, and other NLP applications. Experience with speech recognition, audio classification, and general signal processing techniques. Experience with RAG, VectorDB, GraphDB and Knowledge Graphs Extensive experience with major cloud platforms (AWS, Azure, GCP) for AI/ML deployments. Proficiency in using and integrating cloud-based AI services and tools (e.g., AWS SageMaker, Azure ML, Google Cloud AI). Required Skills: Strong leadership and team management skills. Excellent verbal and written communication skills. Strategic thinking and problem-solving abilities. Adaptability and adapting to the rapidly evolving AI/ML landscape. Strong collaboration and interpersonal skills. Ability to translate market needs into technological solutions. Strong understanding of industry dynamics and ability to translate market needs into technological solutions. Demonstrated ability to foster a culture of innovation and creative problem-solving. Show more Show less

Experience :- 4 to 9 years Company :- ACL Digital Location :- Pune, Balewadi Work Mode: Hybrid Looking for Immediate joiner's Should have experience in NLP, Gen AI, Any Cloud(AWS or Azure), Computer Vision, Python,Deep Learning Excellent verbal and written communication skills. Must Have: Overall 4+ years of experience, out of which in 3+ in AI, ML and Gen AI and related technologies • Proven track record of leading and scaling AI/ML teams and initiatives. • Strong understanding and hands-on experience in AI, ML, Deep Learning, and Generative AI concepts and applications. • Expertise in ML frameworks such as PyTorch and/or TensorFlow • Experience with ONNX runtime, model optimization and hyperparameter tuning. • Solid Experience of DevOps, SDLC, CI/CD, and MLOps practices - DevOps/MLOps Tech Stack: Docker, Kubernetes, Jenkins, Git, CI/CD, RabbitMQ, Kafka, Spark, Terraform, Ansible, Prometheus, Grafana, ELK stack • Experience in production-level deployment of AI models at enterprise scale. • Proficiency in data preprocessing, feature engineering, and large-scale data handling. • Expertise in image and video processing, object detection, image segmentation, and related CV tasks. • Proficiency in text analysis, sentiment analysis, language modeling, and other NLP applications. • Experience with speech recognition, audio classification, and general signal processing techniques. • Experience with RAG, VectorDB, GraphDB and Knowledge Graphs • Extensive experience with major cloud platforms (AWS, Azure, GCP) for AI/ML deployments. Proficiency in using and integrating cloud-based AI services and tools (e.g., AWS SageMaker, Azure ML, Google Cloud AI). Soft Skills • Strong leadership and team management skills. • Strategic thinking and problem-solving abilities. • Adaptability and adapting to the rapidly evolving AI/ML landscape. • Strong collaboration and interpersonal skills. • Ability to translate market needs into technological solutions. • Strong understanding of industry dynamics and ability to translate market needs into technological solutions. • Demonstrated ability to foster a culture of innovation and creative problem-solving. Show more Show less

Position AI ML Engineer Job Description 2 to 5+ years of experience in understanding the problem statement, data handling/triage, selecting and improving neural network models using deep learning frameworks to solve business problems. Excellent hands-on Coding in Python (mandatory), C/C++ or Java. Experience in developing AI/ML/DL models by using transfer learning or from scratch. Reasonably good knowledge on leading deep learning frameworks like Tensorflow, PyTorch, ONNX, Keras and others. Working experience in computer vision models like Yolo, Mobilenet, Resnet etc. Good understanding and working knowledge of AI/ML/DL on Edge (for e.g. Nvidia Jetson family, Qualcomm, Intel, Rpi). Thorough understanding and experience of DL/AI/ML lifecycle - full neural network pipeline, starting from data collection to model building to experimental framework to data analytics. Developed/optimized various models in computing domain (Video, Statistics , Audio and others). Demonstrated experience in completing data science projects with or without minimal supervision. Must possess conceptual understanding of various modelling techniques, pros and cons of each technique. Added Advantage Proven record of migrating Al/ML/DL models/algorithms to low level platforms. Familiar with optimizing code for minimal usage of CPU and memory. Location: IN-GJ-Ahmedabad, India-Ognaj (eInfochips) Time Type Full time Job Category Engineering Services Show more Show less

You will lead the development of a secure, performance-optimized, and cross-platform desktop proctoring application (Windows/macOS) integrated with webcam, microphone, screen capture, AI monitoring features, and a real-time violation alert system. You will also coordinate with the web development team building the admin panels. Responsibilities Develop a native cross-platform desktop application using Electron, .NET MAUI, or Qt. Implement robust lockdown features —app blocking, clipboard control, screen restrictions, remote access blocking, and offline data protection. Integrate real-time webcam, mic, and screen monitoring using system-level APIs (WebRTC/native). Develop or integrate AI modules for behavior detection: face detection, gaze tracking, object/person detection. Ensure secure authentication (username/password, 2FA), AES-256 encryption , and FERPA/GDPR compliance . Implement lightweight storage and upload strategies for logs, video, screenshots, and violation reports. Optimize for low CPU/RAM consumption on mid-range Windows/macOS devices. Collaborate with backend/API and admin panel teams (React.js, Node.js/Django). Lead debugging, testing, and deployment cycles with version control and CI/CD best practices. Ensure cross-platform stability and UI/UX consistency across macOS 12+ and Windows 10+. Qualifications 4–8 years of hands-on experience in cross-platform desktop application development . Strong command of Electron (JS/TS), .NET MAUI (C#), or Qt (C++/Python) . Experience in desktop-level video/audio/screen capture integration . Practical knowledge of integrating or building AI/ML models locally or through lightweight APIs (OpenCV, TensorFlow Lite, ONNX). Proven experience in security-first application design (encryption, access control, local storage). Experience with JWT/2FA authentication , websocket communication , and real-time data processing. Exposure to AWS S3 , encrypted file storage , and offline data handling . Familiar with agile processes, Jira/Trello, Git, and collaborative team environments. Show more Show less