4,151 Machine Learning Specialist jobs in India
Machine Learning Specialist
Posted 4 days ago
Job Viewed
Job Description
We’re looking for a hands-on ML Lead to drive development of scalable, high-performance GenAI applications, particularly using LLMs , RAG architectures , and prompt engineering . If you thrive in an agile, ownership-driven environment and want to shape foundational systems, this is the role for you.
What You’ll Do
- Lead the design and development of LLM-based applications , with a strong focus on prompt optimization , fine-tuning, and real-world usage.
- Architect and implement RAG pipelines using vector databases (e.g., FAISS, Pinecone) and retrieval frameworks (e.g., LangChain, LlamaIndex).
- Develop robust evaluation frameworks for prompt and model performance, including hallucination detection, latency, and relevance metrics.
- Own the end-to-end ML lifecycle : data pipelines, model experimentation, deployment, and monitoring.
- Work closely with founders, product managers, and engineers to align AI capabilities with core product needs.
- Mentor junior ML and data engineers, helping to grow a high-performing AI team.
- Stay at the forefront of GenAI research and rapidly evaluate and integrate new models and techniques.
Key Skills & Qualifications
Must-Have:
- Strong expertise in LLMs (e.g., OpenAI, Claude, Mistral, Llama, Falcon, Cohere).
- Deep knowledge of Prompt Engineering : prompt tuning, prompt chaining, and instruction design.
- Hands-on experience with RAG pipelines and tools like LangChain , Haystack , LlamaIndex .
- Proficient with vector databases (e.g., FAISS, Pinecone, Weaviate, Chroma).
- Advanced Python skills with ML libraries such as PyTorch , Transformers (Hugging Face) , and OpenAI API .
- Familiarity with MLOps and scalable model deployment practices (e.g., Docker, FastAPI, Streamlit, or Ray Serve).
- Strong grasp of NLP concepts, embeddings, tokenization, and evaluation metrics.
Nice-to-Have:
- Experience in startups or building 0→1 AI products.
- Prior work with multimodal models (text + image/audio).
- Knowledge of data labeling, model safety, and fine-tuning.
Why Join Us?
- Work directly with the founding team on GenAI core technology.
- Build real-world products that impact users daily.
Machine Learning Specialist
Posted 4 days ago
Job Viewed
Job Description
Role: Machine Learning
Experience: 6-8 Years
Location: Mumbai / Ahmedabad / Chennai
- 5+ years of experience with data warehouse technical architectures, ETL/ ELT, reporting/analytic tools, and scripting.
- Extensive knowledge and understanding of data modeling, schema design, and data lakes.
- 4+ years of data modeling experience and proficiency in writing advanced SQL and query performance tuning with on Snowflake in addition to Oracle, and Columnar Databases SQL optimization experience.
- Experience with AWS services including S3, Lambda, Data-pipeline, and other data technologies.
- Experience implementing Machine Learning algorithms for data quality, anomaly detection and continuous monitoring, etc
Machine Learning Specialist
Posted 8 days ago
Job Viewed
Job Description
About the Company : We are seeking a talented and driven Machine Learning Engineer with 2-5 years of experience to join our dynamic team in Chennai. The ideal candidate will have a strong foundation in machine learning principles and extensive hands-on experience in building, deploying, and managing ML models in production environments. A key focus of this role will be on MLOps practices and orchestration, ensuring our ML pipelines are robust, scalable, and automated.
About the Role : A short paragraph summarizing the key role responsibilities.
Responsibilities :
- ML Model Deployment & Management : Design, develop, and implement end-to-end MLOps pipelines for deploying, monitoring, and managing machine learning models in production.
- Orchestration : Utilize orchestration tools (e.g., Apache Airflow, Kubeflow, AWS Step Functions, Azure Data Factory) to automate ML workflows, including data ingestion, feature engineering, model training, validation, and deployment.
- CI/CD for ML : Implement Continuous Integration/Continuous Deployment (CI/CD) practices for ML code, models, and infrastructure, ensuring rapid and reliable releases.
- Monitoring & Alerting : Establish comprehensive monitoring and alerting systems for deployed ML models to track performance, detect data drift, model drift, and ensure operational health.
- Infrastructure as Code (IaC) : Work with IaC tools (e.g., Terraform, CloudFormation) to manage and provision cloud resources required for ML workflows.
- Containerization : Leverage containerization technologies (Docker, Kubernetes) for packaging and deploying ML models and their dependencies.
- Collaboration : Collaborate closely with Data Scientists, Data Engineers, and Software Developers to translate research prototypes into production-ready ML solutions.
- Performance Optimization : Optimize ML model inference and training performance, focusing on efficiency, scalability, and cost-effectiveness.
- Troubleshooting & Debugging : Troubleshoot and debug issues across the entire ML lifecycle, from data pipelines to model serving.
- Documentation : Create and maintain clear technical documentation for MLOps processes, pipelines, and infrastructure.
Qualifications :
- Bachelor's or Master's degree in Computer Science, Data Science, Engineering, or a related quantitative field.
- 2-5 years of professional experience as a Machine Learning Engineer, MLOps Engineer, or a similar role.
Required Skills :
- Strong proficiency in Python and its ML ecosystem (e.g., scikit-learn, TensorFlow, PyTorch, Pandas, NumPy).
- Hands-on experience with at least one major cloud platform (AWS, Azure, GCP) and their relevant ML/MLOps services (e.g., AWS SageMaker, Azure ML, GCP Vertex AI).
- Proven experience with orchestration tools like Apache Airflow, Kubeflow, or similar.
- Solid understanding and practical experience with MLOps principles and best practices.
- Experience with containerization technologies (Docker, Kubernetes).
- Familiarity with CI/CD pipelines and tools (e.g., GitLab CI/CD, Jenkins, Azure DevOps, AWS CodePipeline).
- Knowledge of database systems (SQL and NoSQL).
- Excellent problem-solving, analytical, and debugging skills.
- Strong communication and collaboration abilities, with a capacity to work effectively in an Agile environment.
Machine Learning Specialist
Posted 8 days ago
Job Viewed
Job Description
- Proven experience with JAX and NumPy in real-world ML projects
- Strong understanding of TensorFlow, including internals and model structure
- Experience with migrating models between frameworks and ensuring parity
- Solid grasp of ML training workflows, loop mechanics, and evaluation metrics
- Strong Python programming skills and clean, modular code practices
- Familiarity with ML experiment tracking and reproducibility tools (e.g., MLFlow, Weights & Biases)
Machine Learning Specialist
Posted 8 days ago
Job Viewed
Job Description
We're Hiring: Lead ML Engineer – Generative AI
Pune / Trivandrum | 11:00 AM – 8:00 PM IST | WFH / Hybrid
Join a global deep-tech company shaping the future of enterprise intelligence through Generative AI, MLOps, and cloud-native innovation.
Claidroid Technologies Pvt. Ltd. is seeking an exceptional Lead ML Engineer – GenAI to lead the design, development, and deployment of transformative AI systems for enterprise and infrastructure use cases.
About Claidroid
Claidroid is a rapidly growing technology company with a global footprint across India, Finland, and the US . We specialize in building real-world solutions across:
- Artificial Intelligence, Generative AI & AIOps
- Cloud & Edge Computing
- ServiceNow, DevOps, and ETL Modernization
- Identity & Access Management, Cybersecurity
- Geospatial Intelligence & Digital Twins
We empower enterprises across industries—from smart cities to finance and healthcare —to unlock data-driven transformation.
Role Overview: Lead ML Engineer – GenAI
As a Lead ML Engineer , you will:
Architect and deploy scalable, secure, and high-performing Generative AI solutions
Lead the implementation of LLM agents , RAG architectures , and MLOps pipelines
Oversee full-cycle GenAI product development—from experimentation to production
Integrate automation and performance monitoring into all stages of model lifecycle
Responsibilities
- Provide technical leadership for AI developers and multiple POCs
- Build advanced solutions using LLMs, Diffusion Models, Multimodal AI , and GenAI agents
- Fine-tune, optimize, and monitor models using LangChain, LangGraph, promptflow , etc.
- Deploy models on Azure , leveraging containerization, CI/CD, and infrastructure-as-code
- Implement best practices in LLMOps , model observability , and cost/performance optimization
- Promote ethical and explainable AI practices across all deployments
- Translate technical concepts into business insights for stakeholders and clients
Position Details
- Title : Lead ML Engineer – Generative AI
- Experience : 5–10 years
- Location : Pune / Trivandrum (Currently WFH / Hybrid)
- Shift Timing : 11:00 AM – 8:00 PM IST
- Start : Immediate joiners or <30-day notice preferred
Tech Stack & Skills Required
- ML Engineering, Generative AI, LLMs, RAG, Prompt Engineering
- LangChain, LangGraph, promptflow, semantic kernel, Autogen
- Python, PyTorch/TensorFlow, FastAPI, AsyncIO
- CI/CD pipelines (GitHub Actions), Docker, Kubernetes
- Azure cloud services (preferred), or AWS/GCP
- MLOps, model deployment, monitoring, performance tuning
- Responsible AI principles, bias mitigation, model explainability
What Sets Claidroid Apart?
- Global Projects : Collaborate with teams across Europe, US, and India
- Deep-Tech Focus : Solve real problems in AI, IoT, GIS, and Cybersecurity
- Fast-Paced Innovation : Agile, empowered teams working directly with leadership
- Culture of Learning : R&D-driven environment with strong technical mentorship
- Impactful Work : Build systems that serve smart cities, healthcare, BFSI & beyond
Interested?
Apply immediately
Be part of Claidroid’s journey to engineer the intelligent enterprise.
Machine Learning Specialist
Posted 3 days ago
Job Viewed
Job Description
Experience: 6-8 Years
Location: Mumbai / Ahmedabad / Chennai
5+ years of experience with data warehouse technical architectures, ETL/ ELT, reporting/analytic tools, and scripting.
Extensive knowledge and understanding of data modeling, schema design, and data lakes.
4+ years of data modeling experience and proficiency in writing advanced SQL and query performance tuning with on Snowflake in addition to Oracle, and Columnar Databases SQL optimization experience.
Experience with AWS services including S3, Lambda, Data-pipeline, and other data technologies.
Experience implementing Machine Learning algorithms for data quality, anomaly detection and continuous monitoring, etc
Machine Learning Specialist
Posted 3 days ago
Job Viewed
Job Description
What You’ll Do
Lead the design and development of LLM-based applications , with a strong focus on prompt optimization , fine-tuning, and real-world usage.
Architect and implement RAG pipelines using vector databases (e.g., FAISS, Pinecone) and retrieval frameworks (e.g., LangChain, LlamaIndex).
Develop robust evaluation frameworks for prompt and model performance, including hallucination detection, latency, and relevance metrics.
Own the end-to-end ML lifecycle : data pipelines, model experimentation, deployment, and monitoring.
Work closely with founders, product managers, and engineers to align AI capabilities with core product needs.
Mentor junior ML and data engineers, helping to grow a high-performing AI team.
Stay at the forefront of GenAI research and rapidly evaluate and integrate new models and techniques.
Key Skills & Qualifications
Must-Have:
Strong expertise in LLMs (e.g., OpenAI, Claude, Mistral, Llama, Falcon, Cohere).
Deep knowledge of Prompt Engineering : prompt tuning, prompt chaining, and instruction design.
Hands-on experience with RAG pipelines and tools like LangChain , Haystack , LlamaIndex .
Proficient with vector databases (e.g., FAISS, Pinecone, Weaviate, Chroma).
Advanced Python skills with ML libraries such as PyTorch , Transformers (Hugging Face) , and OpenAI API .
Familiarity with MLOps and scalable model deployment practices (e.g., Docker, FastAPI, Streamlit, or Ray Serve).
Strong grasp of NLP concepts, embeddings, tokenization, and evaluation metrics.
Nice-to-Have:
Experience in startups or building 0→1 AI products.
Prior work with multimodal models (text + image/audio).
Knowledge of data labeling, model safety, and fine-tuning.
Why Join Us?
Work directly with the founding team on GenAI core technology.
Build real-world products that impact users daily.
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