2504 Deep Learning Jobs - Page 16

Team Overview: Join our pioneering Core-LLM platform team, dedicated to pushing the boundaries of Generative AI. We focus on developing robust, scalable, and safe machine learning models, particularly LLMs, SLMs, Large Reasoning Models (LRMs) and SRMs that power cutting-edge ServiceNow products and features. As a Senior Manager, you will lead a talented team of machine learning engineers, shaping the future of our AI capabilities and ensuring the ethical and effective deployment of our technology. What you get to do in this role: Generate and evaluate synthetic data tailored to improve the robustness, performance, and safety of machine learning models, particularly large language models (LLMs). Train and fine-tune models using curated datasets, optimizing for performance, reliability, and scalability. Design and implement evaluation metrics to rigorously measure and monitor model quality, safety, and effectiveness. Conduct experiments to validate model behavior and improve generalization across diverse use cases. Collaborate with engineering and research teams to identify risks and recommend AI safety mitigation strategies. Participate in the development, deployment, and continuous improvement of end-to-end AI solutions. Contribute to architectural and technology decisions related to AI infrastructure, frameworks, and tooling. Promote modern engineering practices including continuous integration, continuous delivery, and containerized workflows. Key qualifications: Experience in using AI Productivity tools such as Cursor, Windsurf, etc. is a plus or nice to have Experience with methods of training and fine-tuning large language models, such

You are an experienced Lead Generative AI Engineer responsible for training, optimizing, scaling, and deploying various generative AI models including large language models, voice/speech foundation models, vision, and multi-modal foundation models using cutting-edge techniques and frameworks. Your role involves architecting and implementing state-of-the-art neural architecture, robust training, and inference infrastructure to efficiently take complex models with billions of parameters to production while optimizing for low latency, high throughput, and cost efficiency. Your key responsibilities include: - Architecting and refining foundation model infrastructure to support optimized AI models deployment focusing on C/C++, CUDA, and kernel-level programming enhancements. - Implementing optimization techniques like quantization, distillation, sparsity, streaming, and caching for model performance enhancements. - Spearheading the development of Vision pipelines to ensure scalable training and inference workflows of billions of parameter foundation models. - Innovating for state-of-the-art architectures involving Panoptic Segmentation, Image Classification, and Image Generation. - Designing, developing, and innovating state-of-the-art large multimodal models. - Executing training and inference processes to minimize latency and maximize throughput utilizing GPU clusters and custom hardware. - Integrating and tailoring frameworks like PyTorch, TensorFlow, DeepSpeed, Lightening, FSDP, and Habana for fast model training and inference. - Enhancing post-deployment mechanisms with exhaustive testing, real-time monitoring, and robustness checks. - Driving continuous improvement initiatives for deployed models with automated pipelines for drift detection and performance degradation. - Leading the charge in model management including version control, reproducibility, and lineage tracking. - Cultivating a culture of high-performance computing and optimization within the AI/ML domain. Qualifications: - Ph.D. with 5+ years or MS with 8+ years of experience in ML Engineering, Data Science, or related fields. - Demonstrated expertise in high-performance computing with proficiency in Python, C/C++, CUDA, and kernel-level programming for AI applications. - Extensive experience in optimizing training and inference for large-scale AI models. - Understanding of Diffusion Models, Variational Autoencoders, Bayesian Modelling, and Reinforcement Learning is beneficial. - Experience in building billions of parameters generative AI foundation models. - Proven success in deploying optimized ML systems on a large scale using cloud infrastructures and GPU resources. - In-depth understanding and hands-on experience with advanced model optimization frameworks and MLOps tools. - Familiarity with contemporary MLOps frameworks and their application in production environments. - Strong grasp of state-of-the-art ML infrastructures, deployment strategies, and optimization methodologies. - Innovative problem-solving skills and collaborative mindset. - Exceptional communication and team collaboration skills.,

Utilize cutting-edge deep learning techniques to develop advanced algorithms for neural rendering using Python and popular deep learning frameworks. Collaborate closely with a team of passionate researchers and developers to address complex challenges in deep learning, including multi-modal image synthesis, audio-visual data fusion, and image/video transformation. Enhance the performance of products, ensuring high levels of accuracy, speed, and scalability, with guidance from senior team members. Integrate developed software, algorithms, and AI models into our products and services, working collaboratively with stakeholders. Maintain the software's security, reliability, and maintainability, following senior team members" guidance. Conduct thorough testing and validation to meet the desired performance. Requirements: - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. - 3+ years of industry or research experience in deep learning and computer vision, focusing on areas such as computational photography, neural talking head synthesis, representation and synthesis of lifelike facial attributes, and video synthesis. - Experience with self-supervised, few-shot, or zero-shot learning techniques for image synthesis, as well as domain adaptation techniques for face image synthesis. - Strong understanding of Generative networks for various use-cases like Super-resolution, Inpainting, etc., and state-of-the-art deepfake algorithms. - Minimum 2 years of relevant experience with generative networks such as Transformers, GANs, Auto-encoders, Diffusion models, etc. - Minimum 1-year experience with Vision Transformers. - Experience with multi-modal image synthesis with audio-visual data. - Proficiency in Python programming and deep learning frameworks like PyTorch or TensorFlow, with at least 3 years of experience. - Experience in developing scalable tools and solutions for real-world computer vision problems or visual effects. - Exceptional problem-solving skills and the ability to work effectively in a team environment. Bonus Qualifications: - MS or Ph.D. in Visual Computing, Computer Vision, Machine Learning, or a related field. - Experience with 3D GANs for human body/face synthesis.,

As a Machine Learning Engineer, you will be responsible for designing and implementing end-to-end ML pipelines using GCP services and ETL tools. Your role will involve deploying and maintaining predictive ML models through containerization (Docker) and orchestration (Kubernetes). It is essential to implement MLOps practices, including CI/CD pipelines using Git, to ensure seamless operations. Additionally, creating and maintaining technical architecture diagrams for GCP service implementations will be part of your routine tasks. Your expertise in Machine Learning and Deep Learning concepts will be crucial for this role. Extensive experience with GCP services, particularly AI/ML offerings, is required to excel in this position. Proficiency in MLOps practices and tools is essential, along with hands-on experience in Docker, Kubernetes, and Git. Furthermore, experience in frontend development and API integration will be beneficial for developing frontend applications that integrate with ML and AI backend services. In this role, you will also be responsible for optimizing big data processing workflows and ML model performance. Knowledge of big data processing and analytics is expected, along with the ability to create clear technical documentation and architecture diagrams to ensure effective communication within the team. Preferred qualifications for this position include Google Cloud certifications, experience with AI and GenAI models and applications, and a background in full-stack development. An understanding of microservices architecture, experience with data pipeline optimization, and proficiency in Python, HTML, and JavaScript will further strengthen your candidacy for this role.,

As a research scientist at AryaXAI, you will be part of a team that is revolutionizing the field of AI with a focus on building explainable, safe, and aligned systems at scale. Our mission is to empower researchers, engineers, and organizations to leverage AI effectively while prioritizing transparency and safety. Our team is driven by a shared passion for innovation, collaboration, and excellence. In our flat organizational structure, everyone contributes actively to our mission, valuing curiosity, initiative, and outstanding performance. In this role, you will tackle advanced challenges in ML explainability, safety, and alignment. You will have the flexibility to specialize in specific areas within ML/DL and address various problem types related to these challenges. Additionally, you will be involved in creating new techniques around ML Observability & Alignment, collaborating with MLEs and SDEs to implement features, ensuring their quality and stability, and managing technical and product documentation. To excel in this position, you should have a solid academic foundation in machine learning and deep learning concepts. Hands-on experience with deep learning frameworks like Tensorflow and PyTorch is essential. You should enjoy working on diverse DL problems that involve different types of training datasets such as textual, tabular, categorical, and images. Proficiency in deploying code in cloud/on-premise environments, strong fundamentals in MLOps, and prior experience with ML explainability methods like LRP, SHAPE, LIME, IG, CEM are required. Ideally, you should have at least 2 years of hands-on experience in Deep Learning or Machine Learning, along with practical experience in implementing techniques such as Transformer models, GANs, and other deep learning paradigms. Join us at AryaXAI where startup culture meets research innovation, driving speed and reliability in AI technologies.,

This is an on-site role for a Generative AI Intern at Diebold Nixdorf in Hyderabad location. The Generative AI Intern will be responsible for developing and implementing AI models, algorithms, and solutions to enhance automation and digitization in the banking and retail sectors. The role involves collaborating with cross-functional teams, conducting research, and staying updated on AI advancements to drive innovation in self-service solutions. Required Qualifications: Proficiency in Machine Learning, Deep Learning, and Natural Language Processing Experience in developing and deploying AI models and algorithms Strong programming skills in Python, TensorFlow, or PyTorch Knowledge of data processing and visualization tools Ability to work collaboratively in a team environment Pursuing Bachelors or Masters degree in Computer Science, Artificial Intelligence, or related field Strong problem-solving and analytical skills Proficiency in Machine Learning, Deep Learning, and Natural Language Processing Experience in developing and deploying AI models and algorithms Strong programming skills in Python, TensorFlow, or PyTorch Knowledge of data processing and visualization tools Ability to work collaboratively in a team environment Pursuing Bachelors or Masters degree in Computer Science, Artificial Intelligence, or related field Strong problem-solving and analytical skills

We are looking for a Storage Services Software engineer to join the block storage group. You will be a member of a team that builds the next generation block storage capabilities. You will work closely with a variety of teams and architects including the networking team, HW team and external customers. You will define the Software architecture and implementation of the most advanced storage services! Services that will need to meet extreme performance and scalability demands! We have crafted a team of extraordinary people stretching around the globe, whose mission is to push the frontiers of what is possible today and define the platform of tomorrow. At NVIDIA, we work, think and learn as a team. We thrive in a deeply strong environment, and were passionate about a culture that demands innovation and the highest standards. The rewards are sweet and include collaborating with some of the smartest people in the industry, an aggressive compensation plan that rewards top performers, and the opportunity to work on products that transform the way people work and play. What you ll be doing: Research and implementation of distributed storage services. Design the storage SW stack of NVIDIA block solution. This includes interface definition and implementation in host and DOCA and a DPU environments. Design of storage related features and accelerations in the framework of DOCA and a DPU Design DPU Storage services orchestration in datacenter What we need to see: B. Sc. , M. Sc. or Ph. D. in Computer Science or related discipline 18+ years of experience in a storage company as senior developer or an architect Ability to quickly adapt to new technology and go deep into new areas Can work independently Strong communication skills Able to work with customers and partners Drive new solutions based on any issues that arise

We are looking for an experienced AI & Generative AI Developer who can work across the AI spectrum from classical machine learning models to cutting-edge Generative AI applications. The role demands strong experience in building ML models using regression, classification, and tree-based algorithms, along with hands-on exposure to LLMs and generative frameworks like GPT, Stable Diffusion, and LangChain. Key Responsibilities Classical AI/ML Design and implement supervised and unsupervised ML models including: Linear Regression, Logistic Regression Decision Trees, Random Forest, XGBoost Naive Bayes, K-Means, SVM, PCA, etc. Preprocess and analyse structured/tabular datasets Evaluate models using metrics like accuracy, precision, recall, ROC-AUC, and RMSE Build predictive models , deploy them into production, and monitor performance Collaborate with business teams to translate requirements into ML use cases Generative AI (GenAI) Build and fine-tune LLMs (e.g., GPT, LLaMA, PaLM) for summarisation, Q&A, document generation, etc. Implement prompt engineering , RAG pipelines , and vector database integrations Use libraries like Hugging Face Transformers, LangChain, and LlamaIndex Develop APIs to expose GenAI models in real-time apps Optimise model inference using quantisation, batching, etc. Ensure safe, explainable, and bias-free output in alignment with AI ethics guidelines Required Skills & Qualifications Bachelor s or Master s in Computer Science, Data Science, Statistics, or related field Strong programming skills in Python , with experience in NumPy, Pandas, Scikit-learn Proficiency in classical ML algorithms (regression, trees, naive Bayes, etc.) Experience with LLM frameworks like OpenAI API, Hugging Face, and LangChain Understanding of transformer architecture , NLP, embeddings, and tokenisation Familiarity with REST API development using FastAPI/Flask Exposure to cloud platforms (AWS/GCP/Azure) and Docker/Kubernetes Preferred / Nice to Have Experience with deep learning (TensorFlow, PyTorch) Exposure to image/audio/video generation using models like DALL E, Stable Diffusion, Whisper Familiarity with RAG , LLMOps , and vector stores (FAISS, Pinecone, Weaviate) Knowledge of MLOps pipelines , model monitoring , and CI/CD for ML

Job Requirements Summary: We are seeking skilled Python developers to assist in a large-scale code conversion project. The project involves transforming a legacy codebase of image processing and deep learning computer vision algorithms from MATLAB to Python. The initial conversion has been performed using state of the art AI capabilities (LLMs), and we now require human expertise to creating a working code base. Duties and Responsibilities: Review and compare LLM converted Python code against original MATLAB code Debug syntax errors and correct logical inconsistencies in the Python code Ensure output consistency between MATLAB and Python implementations Implement proper error handling and logging mechanisms Develop comprehensive unit tests and integration tests Create clear and concise documentation for the converted code Optimize code for performance and readability wherever necessary Collaborate with team members to ensure end-to-end functionality Prepare code for containerization using Docker Adhere to best practices in software development and version control Work Experience Knowledge, Skills and Abilities: Strong proficiency in Python programming with 6+ years of experience Familiarity with MATLAB syntax and conventions Strong problem-solving and debugging skills Experience with version control systems (e. g. , Git) Familiarity with Docker and containerization concepts Experience in code conversion projects Familiarity with scientific computing libraries (e. g. , NumPy, SciPy) Knowledge of software testing frameworks (e. g. , pytest) Experience with continuous integration and deployment (CI/CD) pipelines Understanding of software development best practices and design patterns Implement proper logging mechanisms for easier debugging and monitoring Create comprehensive unit tests and integration tests to ensure code reliability Develop clear and concise documentation, including inline comments and README files Optimize code for performance, considering Python-specific best practices Ensure code adheres to PEP 8 style guidelines Implement type hinting for improved code readability and maintainability Create requirements. txt files for each repository to manage dependencies Participate in code reviews to maintain high code quality standards Provide regular progress reports and participate in team meetings Optional requirements: Experience with image processing and computer vision libraries (e. g. , OpenCV, scikit-image) Knowledge of deep learning frameworks (e. g. , TensorFlow, PyTorch) Understanding of mathematical concepts related to image processing and computer vision

Job Requirements We are seeking an experienced AI Developer to join our team and contribute to the development of cutting-edge solutions for defect detection in automotive manufacturing. The role involves leveraging AI technologies to inspect and identify defects in cars using image-based analysis. Key Responsibilities: AI Model Development: - Design, develop, and optimize deep learning models for defect detection using image data. - Implement segmentation techniques to localize small defect areas in addition to classification and detection. Data Preparation and Augmentation: - Utilize online augmentation techniques to enhance limited datasets. - Work with simulated data to demonstrate proof-of-concept for industrial defect detection. Edge AI Deployment: - Deploy AI models on edge devices using Intel Architecture, ensuring compatibility with existing hardware. - Optimize inference performance using tools. Performance Optimization: - Achieve real-time processing with low latency - Ensure high accuracy in defect detection of 1mm size Collaboration and Testing: - Collaborate with domain experts to fine-tune model thresholds for minimizing overkill and underkill. - Test AI solutions on SEM/Optical inspection images to validate performance. Work Experience - Proficiency in Python and experience with AI Models like Yolo. - Strong knowledge of deep learning architectures. - Experience with Edge AI deployment. - Familiarity with industrial defect datasets and augmentation techniques. - Excellent problem-solving skills and ability to optimize AI models for real-time applications.

We are seeking a highly experienced and motivated Senior Data Science Engineer - Computer Vision Specialist with 9-12 years of relevant experience to join our advanced analytics team. This individual will take a leadership role in building and optimizing visual intelligence solutions with a primary focus on Face Recognition and Automatic Number Plate Recognition (ANPR) , while also contributing to broader data analytics initiatives including client collaboration and third-party data management. Key Responsibilities: Lead the design, development, and deployment of advanced computer vision systems, including face recognition, ANPR, and real-time video/image analytics. Architect scalable, high-performance data pipelines to manage large-scale image and video datasets. Guide model experimentation, development, and optimization using deep learning frameworks such as TensorFlow, PyTorch, and Nvidia Deepstream. Provide technical mentorship to junior team members and review solution architectures. Collaborate with cross-functional teams to integrate computer vision capabilities into enterprise platforms and edge devices like Nvidia Jetson. Ensure end-to-end quality and performance of deployed models in production environments. Conduct applied research to identify and implement state-of-the-art vision technologies. Drive model explainability, documentation, and stakeholder reporting. Client Collaboration: Lead data discovery sessions with clients to understand their business needs, identify data sources, and define data strategies. Work closely with stakeholders to align analytics solutions with organizational goals. Data Transformation and Governance: Perform data extraction, transformation, and loading ( ETL ) using tools like Python, SQL, and cloud platforms. Enable and facilitate discussions around data governance, ensuring compliance, quality, and security standards. Third-Party Data Management: Integrate, analyze, and manage third-party datasets relevant to the oil and gas industry, ensuring seamless integration with client systems. Analytics and Market Intelligence: Conduct advanced analytics to deliver actionable insights for market intelligence, operational efficiency, and strategic decision-making. Required Skills and Qualifications: Bachelor's, Master's, or Ph.D. in Computer Science, Data Science, or a related field. 9–12 years of experience in data science, machine learning, and computer vision. Expertise in Python and machine learning libraries such as OpenCV, TensorFlow, PyTorch. Proven experience in developing face recognition and ANPR systems, ideally with Nvidia Deepstream and Jetson platforms. In-depth knowledge of computer vision concepts including object detection, OCR, and image segmentation. Strong background in ETL processes, data governance, and database querying using SQL. Familiarity with cloud ML platforms like AWS SageMaker, GCP AI, or Azure ML. Hands-on experience with Git, Docker, and CI/CD pipelines. Excellent communication skills and experience presenting technical content to non-technical stakeholders. Preferred Qualifications: Experience with OCR and integration with vision systems. Exposure to real-time video analytics and multi-camera environments. Contributions to open-source projects or published research in computer vision or AI. Understanding of data privacy, ethical AI practices, and secure handling of visual data.

We are looking for a senior-level Data Scientist to lead the design and development of cutting-edge machine learning solutions that power InMobi s Accelerate platform. You ll be solving highly impactful problems around budget optimization, creative scoring, campaign recommendations, and cross-channel attribution in a fast-paced, AI-first environment. Responsibilities: Lead the design and deployment of ML models across campaign recommendation, budget allocation, and creative optimization. Develop robust pipelines for data preprocessing, feature engineering, model training, validation, and deployment. Build and fine-tune predictive models using supervised/unsupervised learning, deep learning, and reinforcement learning. Partner with product managers and engineers to translate business goals into ML problem statements. Own model performance monitoring, explainability, retraining schedules, and feedback loops for continuous learning. Collaborate with MLOps and platform teams for scalable deployment (batch + real-time). Contribute to experimentation frameworks, model versioning, and reproducibility. Qualifications: 5-8 years of experience in Data Science/Machine Learning roles, preferably in AdTech, MarTech, or B2B SaaS. Strong foundations in statistics, optimization, time-series forecasting, and ML algorithms. Proficiency in Python (NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow) and SQL. Hands-on experience with ML lifecycle tools (MLflow, Airflow, SageMaker, Vertex AI, etc.). Experience working with ad performance data, user behavior modeling, attribution models, or recommender systems. Bonus: Experience with causal inference, LTV modeling, or generative AI for text/image.

We are looking for people who can explore new ideas, design and implement next-generation architectures/techniques in image/video, language, audio and multimodal space. You should be motivated to push the boundaries not just in state-of-the-art performance, but also in balancing performance in terms of inference speed and compute resource usage. You will collaborate with a multidisciplinary team of researchers, engineers, and data scientists to develop and deploy practical and scalable solutions to real-world challenges in areas such as domain based instruction fine-tuning LLMs, improving text to image and foundational models, to name a few. Your work will have a direct impact on the development of our AI-driven products and services. Job Location: Bangalore, Pune, Mumbai, Gurgaon, Chennai Job Responsibilities: Conduct research and stay up to date with the latest advancements in computer vision, NLP, deep learning, RL and related fields. Design and develop novel and next generation of deep learning algorithms, models, and techniques to address specific problem domains Document research findings, methodologies, and experimental results in technical reports, blogs and papers. Publish research findings and contribute to conferences, workshops, and other scientific forums. Collaborate with engineering and business teams on model deployment and customised training respectively. Qualifications: Extensive understanding of advanced DL or generative architectures/techniques like diffusion architectures, attention models, LLMs, SAM, RLHF etc Have a track record of coming up with new ideas or improving upon existing ideas in deep learning quickly, demonstrated by accomplishments such as first author publications or published/deployed projects or impactful blogs. Ability to efficiently work on a modern deep learning stack, such as Python, PyTorch, and GPU-enabled compute, eg writing non-trivial custom architecture in Pytorch. Ability to iterate quickly on open-source code-bases with attention to backwards compatibility, usability, and readability. Creative, fast-paced executor, detail-oriented, eager to learn, acquire new skills. Ability to work effectively in a collaborative team environment and take ownership. Strong belief in a positive-sum game, valuing cooperation and collaboration over zero-sum competition.

Job Requirements Summary Were seeking an experienced MLOps Engineer to build and maintain our computer vision infrastructure on AWS. The ideal candidate will develop model training pipeline, a comprehensive image data lake with advanced search capabilities, implement active learning pipelines for efficient annotation, and create frameworks enabling customers to deploy their own deep learning models. This role combines MLOps expertise with data engineering to create scalable, production-ready computer vision systems. Responsibilities: Design and implement end-to-end computer vision ML training pipelines on AWS SageMaker for model training, validation, deployment, and monitoring Architect and build a scalable image data lake solution enabling multi-modal search capabilities (structured metadata, image-to-image, text-to-image) along with data upload capability from edge devices Develop vector embedding pipelines for visual content using AWS services and deep learning frameworks Create APIs for seamless integration with third-party annotation services and automated dataset creation Implement active learning pipelines that intelligently select high-value images for annotation, optimizing annotation ROI Build data quality and validation frameworks to ensure consistency across the annotation lifecycle Develop infrastructure automation using AWS CloudFormation/CDK for scalable deep learning workflows Establish monitoring systems for data drift, annotation quality, and model performance Create skeleton frameworks and templates enabling customers to deploy their own deep learning models Optimize storage and retrieval mechanisms for large-scale image repositories Work Experience Requirements: Bachelors or Masters degree in Computer Science, Engineering, or related field 5+ years of experience in MLOps or ML Engineering with focus on computer vision applications Experience building data lakes or large-scale data repositories for unstructured data Strong understanding of vector databases, embedding models, and similarity search algorithms Hands-on experience with AWS services (S3, SageMaker, Lambda, Step Functions, Glue) Proficiency in Python and experience with PyTorch or TensorFlow Experience implementing active learning systems for optimizing annotation workflows Knowledge of RESTful API design and integration with third-party services Familiarity with annotation tools and workflows for computer vision datasets Experience with containerization (Docker) and orchestration (Kubernetes/EKS) Understanding of data governance and security best practices for sensitive image data

Candidate should be experienced in Data Science, Pyton, AI, Machine Learning & Deep Learning Candidate should have prior experience or exposure as a trainer. Contact- 9205783661

Were Hiring: Lead - AI/ML Engineering at Coschool Location: Nanakramguda, Hyderabad Employment Type: Full-Time Experience: 7+ Year s Join Coschool to revolutionize learning with A I. At Coschool, were building a next-gen EdTech platform thats reshaping how students learn. Our AI-first platform is designed to empower educators and support students in achieving their best. We’re now looking for a Manager – AI/ML Engineering to lead and scale our AI initiatives and shape the future of intelligent learning syste ms. What You’ll Do (Key Responsibilities): Lead and mentor a high-performing team of AI/ML engineers. Research, prototype, and develop robust ML models, including deep learning and GenAI solutions. Oversee the full AI/ML project lifecycle — from data preprocessing to deployment and monitoring. Guide the team in training, fine-tuning, and deploying LLMs using methods like distillation, supervised fine-tuning, and RLHF. Collaborate with product managers, engineers, and leadership to translate business problems into ML solutions. Ensure the scalability, reliability, and security of AI systems in production. Define and enforce best practices in MLOps, model management, and experimentation. Stay on the cutting edge of AI by exploring and applying emerging trends and technologies. You’re a Great Fit If You Have: 4 to 8 years of experience in building AI/ML solutions, with at least 1 years in a leadership or managerial role. Strong foundation in machine learning, deep learning, and computer science fundamentals. Hands-on experience deploying AI models in production using frameworks like PyTorch, TensorFlow, and Scikit-learn. Proficiency with cloud ML platforms (AWS SageMaker, Google AI, Azure ML). Solid understanding of MLOps tools and practices for model lifecycle management. Experience with LLM fine-tuning and training methodologies. Excellent problem-solving, communication, and people management skills. A proactive mindset and passion for innovation and mentorship. Preferred Skills: Experience working with generative AI frame works. A portfolio or track record of creative AI/ML applications. Familiarity with tools for LLM orchestration and retrieval-augmented generation (RAG). Why Coschool? Real Impact: Build solutions that directly affect the lives of millions of students. Autonomy: Enjoy the freedom to innovate and execute with a clear mission in mind. Growth: Work in a fast-paced, learning-focused environment with top talent. Vision: Be part of a purpose-driven company that combines decades of educational excellence with cutting-edge AI.

Were Hiring: Manager AI/ML Engineering at Coschool Location: Nanakramguda, Hyderabad Employment Type: Full-Time Experience: 7+ Year s Join Coschool to revolutionize learning with A I. At Coschool, we’re building a next-gen EdTech platform that’s reshaping how students learn. Our AI-first platform is designed to empower educators and support students in achieving their best. We’re now looking for a Manager – AI/ML Engineering to lead and scale our AI initiatives and shape the future of intelligent learning syste ms. What You’ll Do (Key Responsibilities): Lead and mentor a high-performing team of AI/ML engineers. Research, prototype, and develop robust ML models, including deep learning and GenAI solutions. Oversee the full AI/ML project lifecycle — from data preprocessing to deployment and monitoring. Guide the team in training, fine-tuning, and deploying LLMs using methods like distillation, supervised fine-tuning, and RLHF. Collaborate with product managers, engineers, and leadership to translate business problems into ML solutions. Ensure the scalability, reliability, and security of AI systems in production. Define and enforce best practices in MLOps, model management, and experimentation. Stay on the cutting edge of AI by exploring and applying emerging trends and technologies. You’re a Great Fit If You Have: 7 to 12 years of experience in building AI/ML solutions, with at least 2 years in a leadership or managerial role. Strong foundation in machine learning, deep learning, and computer science fundamentals. Hands-on experience deploying AI models in production using frameworks like PyTorch, TensorFlow, and Scikit-learn. Proficiency with cloud ML platforms (AWS SageMaker, Google AI, Azure ML). Solid understanding of MLOps tools and practices for model lifecycle management. Experience with LLM fine-tuning and training methodologies. Excellent problem-solving, communication, and people management skills. A proactive mindset and passion for innovation and mentorship. Preferred Skills: Experience working with generative AI frame works. A portfolio or track record of creative AI/ML applications. Familiarity with tools for LLM orchestration and retrieval-augmented generation (RAG). Why Coschool? Real Impact: Build solutions that directly affect the lives of millions of students. Autonomy: Enjoy the freedom to innovate and execute with a clear mission in mind. Growth: Work in a fast-paced, learning-focused environment with top talent. Vision: Be part of a purpose-driven company that combines decades of educational excellence with cutting-edge AI.

Job description We're looking for a highly skilled and visionary Agentic AI Implementation Engineer who can design, build, and deploy intelligent systems using Agentic techniques. This role will involve creating autonomous or semi-autonomous agents powered by LLMs that are capable of task planning, contextual decision-making, and iterative information retrieval. You'll work at the intersection of advanced prompt engineering, tool orchestration, and multi-step reasoning, with a strong focus on performance, scalability, and user-centric design. Key Responsibilities Architect and implement agentic workflows using RAG pipelines, LLM agents, and external tool integrations. Design modular, agentic systems that include planning, memory, tool use, and context-aware reasoning. Develop and optimize custom GPTs using advanced prompt engineering and OpenAI\u2019s custom instructions, functions, and APIs. Integrate knowledge bases, vector stores (e.g., FAISS, Pinecone, Weaviate), and APIs into a cohesive Agentic RAG architecture. Fine-tune agent behaviors for various real-world applications (e.g., customer support, research assistants, code agents). Collaborate closely with product managers, UX designers, and backend engineers to ship scalable and robust solutions. Rapidly prototype ideas, run LLM experiments, and iterate on designs using both quantitative and qualitative metrics. Monitor system performance, detect and address reasoning failures, hallucinations, and retrieval mismatches. Stay updated with the latest research and advancements in Agentic AI, RAG, tool use, and autonomous agents. Must-Have Skills Strong expertise in Agentic RAG frameworks such as LangGraph, AutoGPT, CrewAI, LangChain Agents Proven ability to design and implement custom GPTs using advanced prompt strategies and OpenAI API (functions, tools, memory). Hands-on experience with vector databases (e.g., Cosmos DB, Pinecone, ChromaDB), embeddings, and semantic search. Deep understanding of retrieval augmentation , context compression, multi-hop querying, and memory management. Fluency in Python and experience with modern LLM tooling (e.g., LangChain, LlamaIndex). Strong systems thinking and ability to balance trade-offs between model performance, latency, and accuracy. Comfortable with fast-paced, iterative environments and exploratory development. Desired Skills Experience with autonomous agents and frameworks like AutoGen, OpenAgents, or BabyAGI. Understanding of AI safety, ethics, and control mechanisms in agentic systems. Familiarity with evaluation techniques for LLM pipelines (e.g., hallucination detection, prompt testing frameworks).

Company name: Tier 1 TOP GLOBAL MNC IT company. Location: Bangalore, Pune, ( Hybrid ) As a level in our Consultant/Senior Consultant/Manager youll build and nurture positive working relationships with teams and clients with the intention to exceed client expectations: - We are seeking skilled ML-Ops Manager / Senior Consultants to implement and manage ML-Ops frameworks for various industries. The ideal candidates will have a minimum of 8+ Years (Manager)/4-7 Years of experience (Senior Consultant) in Designing, Implementing, and leading ML-Ops frameworks. In this role, you will be responsible for the deployment, testing, and continuous integration of machine learning models while working with cross-functional teams. Following are the Key requirements: Collaborate with data scientists, developers, and infrastructure teams to ensure seamless integration of machine learning models into production environments. Develop and implement ML-Ops best practices to streamline the end-to-end machine learning lifecycle, from model training and testing to deployment and monitoring. Design, build, and maintain scalable and reliable machine learning pipelines for data ingestion, preprocessing, feature engineering, model training, and deployment. Implement and manage continuous integration and continuous deployment (CI/CD) processes for machine learning models. Monitor the health and performance of deployed models, identifying and addressing issues related to data drift, model degradation, and performance bottlenecks. Automate model retraining and deployment processes to ensure models remain up to date with changing data and requirements. Collaborate with cross-functional teams to ensure data security, compliance, and privacy standards are met throughout the ML-Ops lifecycle. Drive improvements in the machine learning infrastructure by evaluating new tools, technologies, and processes. Participate in on-call rotations to address critical system issues as they arise. Additional Preferred Skills: Consulting/Strategy, Analytics and M&A(SAMA)/AI&Data |Consultant/Senior Consultant/Manager Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK stack) for tracking model performance and system health. Knowledge of machine learning model monitoring and management platforms. Background in distributed computing and parallel processing. Domain expertise in Telecom, Retail / BFSI, Marketing, Life science, Manufacturing etc. Desired qualifications Bachelor's or Master's degree in Computer Science, Engineering, Data Science, or related field. Proven experience in deploying and managing machine learning models in production environments. Strong programming skills in languages such as Python, and experience with relevant libraries/frameworks (e.g., TensorFlow, PyTorch, scikit-learn). Hands-on experience with containerization technologies such as Docker and orchestration platforms like Kubernetes. Proficiency in designing and optimizing data pipelines for large-scale data processing and machine learning. Familiarity with cloud platforms (e.g., AWS, Azure, Google Cloud) and services for ML model deployment and management. Experience with version control systems (e.g., Git) and CI/CD tools (e.g., Jenkins, GitLab CI/CD). Strong understanding of DevOps principles and practices, and the ability to collaborate effectively with cross-functional teams. Excellent problem-solving skills and the ability to diagnose and resolve complex technical issues. Strong communication skills, both written and verbal, to effectively convey technical information to non-technical stakeholders.

Develop & optimize VTON AI models using PyTorch/TensorFlow Work with GANs, pose estimation, segmentation Deploy models with CUDA, TensorRT, ONNX Integrate AI into production systems Bonus: Experience in fashion tech or try-on solutions Requirements: Strong Python skills & deep learning experience Computer vision & image processing expertise Hands-on with GPU acceleration tools Knowledge of FastAPI, Flask, or TensorFlow Serving for deployment Role & responsibilities

interested candidates share cv to dikshith.nalapatla@motivitylabs.com Total Experience: 5+ years Relevant:5+years Role: Python Developer with AI ML (Data Scientist) Skills: Python, FastAPI/Flask/Django anyone would be fine GenAI and LLM Experience is a must have, at least 2 projects PyTorch or Tensorflow, scikit-learn, pandas, numpy Cloud technologies - at least 1 out of AWS, GCP, Azure Database - SQL (MySQL, PostGres, SQL server any one would be fine), NoSQL Experience is a good to have Key Responsibilities: Python Web Development: Design, develop, and maintain Python-based web applications using Django or Flask frameworks. Ensure code is efficient, scalable, and maintainable. Cloud Integration: Integrate applications with cloud services, such as AWS, Azure, or Google Cloud, to leverage scalability and reliability. Deploy and manage applications on cloud infrastructure. Containerization: Utilize containerization technologies like Docker to package applications and ensure consistent deployment across different environments. Coding Best Practices: Follow coding best practices, maintain clean and well-documented code, and conduct code reviews to ensure code quality and adherence to coding standards. Software Development Principles: Apply software development principles such as SOLID, DRY (Don't Repeat Yourself), and KISS (Keep It Simple, Stupid) to create efficient and maintainable code. Database Integration: Work with various databases (SQL and NoSQL) to design and implement data models and efficient database queries. API Development: Create RESTful APIs using Django REST framework or similar tools to facilitate data exchange between front-end and back-end systems. Security: Implement security best practices, including authentication, authorization, and data encryption, to protect applications against security vulnerabilities. Performance Optimization: Identify and resolve performance bottlenecks in applications by profiling code and applying optimization techniques. Testing: Develop unit tests and integration tests to ensure the reliability and functionality of web applications. Documentation: Create and maintain technical documentation, including code comments, system architecture diagrams, and API documentation. Continuous Integration/Continuous Deployment (CICD): Set up CICD pipelines to automate build, testing, and deployment processes, ensuring rapid and reliable releases. Code Versioning: Use code versioning systems like Git for collaborative development and code management. Monitoring and Logging: Implement monitoring and logging solutions to track application performance and troubleshoot issues proactively. Good to have: Programming skills in leveraging data manipulation, analysis, and visualization libraries (e.g., pandas, NumPy, Matplotlib, seaborn) to deliver actionable insights and data-driven solutions. Familiarity with big data technologies and cloud platforms is a plus. Familiarity with MLOps platforms like MLFlow. Thorough knowledge of database systems, SQL, and NoSQL databases. Qualifications: Bachelor's degree in Computer Science, Software Engineering, or a related field (Master's degree preferred). Extensive experience in Python web development with Django or Flask. Strong knowledge of cloud services (e.g., AWS, Azure, Google Cloud) and cloud deployment. Good Experience in AI ML interested candidates share cv to dikshith.nalapatla@motivitylabs.com Total Experience: Relevant Experience: Gen AI Experience: ML Experience: Current Role / Skillset: Current CTC: Fixed: Variables(if any): Bonus(if any): Payroll Company(Name): Client Company(Name): Expected CTC: Official Notice Period: Serving Notice (Yes / No): CTC of offer in hand: Last Working Day (in current organization): Location of the Offer in hand: Willing to work from office: ************* 5 DAYS WORK FROM OFFICE MANDATORY ****************

As a Senior Vice President, Digital Delivery Practice Lead, you will be responsible for driving the design, development, and deployment of cutting-edge AI solutions. You will lead a talented team of AI engineers and data scientists, collaborate with cross-functional groups, and ensure the successful execution of AI projects from concept through delivery. Your extensive experience in AI technologies, software engineering, leadership, and project delivery will be crucial in creating impactful AI-driven solutions. The role emphasizes setting up best practices in software engineering, including CI/CD pipelines, version control, automated testing, and cloud-native design patterns such as microservices and serverless architecture. Applying DevOps principles to both cloud and AI application development will ensure efficient, reliable, and scalable delivery. You will oversee the entire lifecycle of cloud-based and AI applications, defining the vision, leading the design and development process, and ensuring successful deployment and post-launch performance monitoring. Anticipating future needs and adapting strategies to incorporate evolving cloud and AI technologies will be essential. Your responsibilities include overseeing the end-to-end lifecycle of AI application development, guiding the integration of AI models into production systems, collaborating with business stakeholders to translate requirements into technical solutions, and leveraging state-of-the-art AI methodologies like machine learning, deep learning, and NLP to address complex challenges. You will manage the delivery of AI projects, implement agile methodologies and DevOps practices, lead the architecture and scaling of efficient and secure AI solutions, and collaborate with cross-functional teams to drive value and address business needs. In addition to project delivery and execution, you will work closely with product managers, business analysts, and technical teams to ensure seamless integration of AI applications, update senior leadership on project progress, and foster a high-performance culture within your team. Staying ahead of industry trends, promoting the adoption of AI solutions, and continuously refining processes to optimize the AI development lifecycle will be key focus areas. Ensuring compliance with data privacy regulations and ethical AI practices, maintaining high standards of performance, quality, and accuracy in AI applications, and overseeing post-deployment value delivery are also part of your responsibilities. Qualifications for this role include 20 years of experience in delivering software engineering and AI solutions, technical delivery of large digital projects, hands-on experience with cloud data AI and full stack development, in-depth understanding of technical architecture, and the ability to assess and blueprint clients" technology stack. A bachelor's degree in computer science or related field, with an advanced degree from a premiere institute, proven leadership track record in delivering AI/ML and digital solutions at scale, strong business acumen, excellent communication skills, and the ability to thrive in a fast-paced environment are required. If you meet the qualifications and are ready to take on this challenging and rewarding role, we look forward to receiving your application.,

As a Junior Data Scientist specializing in Generative AI, you will have the exciting opportunity to explore new problems, drive innovation, and apply advanced machine learning techniques and programming skills, especially in Python. Your primary role will involve enhancing the analytics backend flagship products and contributing to the advancement of knowledge discovery solutions. This position is ideal for individuals who are passionate about learning, creative problem-solving, and thrive in a dynamic environment. To be eligible for this role, you should have a Bachelor's degree in computer science or a related field OR a Master's degree in statistics, along with 2-6 years of experience in the Analytics/Data Science domain. Proficiency in programming languages such as Python is essential, as well as experience with Generative AI techniques and tools. You should also be familiar with data imputation, data cleaning, outlier handling, cloud platforms like AWS, AI/ML services, and databases/tools such as SQL. Desirable technical skills include expertise in NLP and Generative AI concepts/methods/techniques, such as Prompt design/engineering, Retrieval Augmented Generation (RAG), Corrective RAG, Knowledge Graph-based RAG using GPT4o, Fine-tuning through LORA/QLORA, and Multi-agentic frameworks for RAG. A strong understanding of Deep Learning methods, Machine Learning techniques, Ensemble methods, Support Vector Machines, and NLP is also preferred. Your specific responsibilities will include translating business requirements into actionable analytical plans, identifying appropriate data sources, resolving data discrepancies, delivering projects and proof-of-concept initiatives, contributing to technical and analytics architecture development, implementing analytical frameworks and data pipelines, coordinating with cross-functional teams, and delivering production-ready models and solutions. You will also be responsible for monitoring success metrics, staying informed about new trends in Generative AI, and integrating relevant advancements into solutions. With 8-11 years of experience, your primary skill will be AI/ML Development, with additional expertise in Python, TensorFlow, and PyTorch. The company you will be working for, Infogain, is a human-centered digital platform and software engineering company based in Silicon Valley. Infogain engineers business outcomes for Fortune 500 companies and digital natives across various industries using technologies like cloud, microservices, automation, IoT, and artificial intelligence. As an Infogain employee, you will accelerate experience-led transformation in the delivery of digital platforms.,

The ideal candidate for this position will be responsible for understanding business problems and formulating analytical solutions. You will apply machine learning, data mining, and text mining techniques to develop scalable solutions for various business challenges. You will also be involved in speech to text translation for Video/Audio NLP Analysis and generative AI application for Market Research data. Additionally, you will solve problems using advanced AI techniques, including GenAI methods, by designing NLP/LLM/GenAI applications/products with robust coding practices. Experience in LLM models like PaLM, GPT4, and Mistral is preferred. You will be expected to train, tune, validate, and monitor predictive models, as well as analyze and extract relevant information from large amounts of historical business data in structured and unstructured formats. Furthermore, you will establish scalable, efficient, automated processes for large-scale data analyses and develop and deploy Data Science models on cloud platforms like GCP, Azure, and AWS. Working with large, complex data sets using tools such as SQL, Google Cloud Services, Hadoop, Alteryx, and Python will be part of your daily responsibilities. Preferred qualifications for this role include 2+ years of experience in market research, data mining, statistical analysis, Gen AI, modeling, deep learning, optimization, or similar analytics. Additionally, having 2+ years of work experience with Python, SQL, and/or visualization/dashboard tools like Tableau, PowerBI, or Qliksense is desired. Comfort with working in an environment where problems are not always well-defined and the ability to effectively advocate technical solutions to various audiences are also important. Candidates with 3-4 years of industry experience and a Bachelor's or Master's degree in a quantitative field such as Statistics, Computer Science, Economics, Mathematics, Data Science, or Operations Research are required for this position. You should have 3+ years of experience using SQL for acquiring and transforming data, as well as experience with real-world data, data cleaning, data collection, or other data wrangling challenges. Knowledge in fundamental text data processing and excellent problem-solving, communication, and data presentation skills are essential. Moreover, you should be flexible to work on multiple projects/domains/tools, possess collaborative skills to work with business teams, and be comfortable coding in Tensorflow and/or Pytorch, Numpy, and Pandas, Scikit-learn. Experience with open-source NLP modules like SpaCy, HuggingFace, TorchText, fastai.text, and others is beneficial. Proven quantitative modeling and statistical analysis skills, along with a proactive and inquisitive attitude towards learning new tools and techniques, are highly valued.,

Genpact is a global professional services and solutions firm with over 125,000 employees in 30+ countries. Driven by curiosity, entrepreneurial agility, and the desire to create value for clients, we serve leading enterprises worldwide with deep business knowledge, digital operations services, and expertise in data, technology, and AI. Our purpose is the relentless pursuit of a world that works better for people. We are currently seeking a Business Analyst - Data Scientist to join our team. In this role, you will be responsible for developing and implementing NLP models and algorithms, extracting insights from textual data, and working collaboratively with cross-functional teams to deliver AI solutions. Responsibilities: Model Development: - Proficiency in various statistical, ML, and ensemble algorithms - Strong understanding of Time series algorithms and forecasting use cases - Ability to evaluate model strengths and weaknesses for different problems Data Analysis: - Extracting meaningful insights from structured data - Preprocessing data for ML/AI applications Collaboration: - Working closely with data scientists, engineers, and business stakeholders - Providing technical guidance and mentorship to team members Integration and Deployment: - Integrating ML models into production systems - Implementing CI/CD pipelines for continuous integration and deployment Documentation and Training: - Documenting processes, models, and results - Providing training and support on NLP techniques and tools to stakeholders Qualifications: Minimum Qualifications / Skills: - Bachelor's degree in computer science, Engineering, or a related field - Strong programming skills in Python and R - Experience with DS frameworks (SKLEARN, NUMPY) - Knowledge of machine learning concepts and frameworks (TensorFlow, PyTorch) - Strong problem-solving and analytical skills - Excellent communication and collaboration abilities Preferred Qualifications / Skills: - Experience in Predictive Analytics and Machine Learning techniques - Proficiency in Python/R/Any other open-source programming language - Knowledge of visualization tools such as Tableau, Power BI, Qlikview, etc. - Applied statistics skills - Experience with big data technologies (Hadoop, Spark) - Knowledge of cloud platforms (AWS, Azure, GCP) If you are passionate about leveraging your skills in data science and analytics to drive innovation and value creation, we encourage you to apply for this exciting opportunity at Genpact.,