Data Science Engineer - Machine Learning & Generative AI

• Design, develop, and deploy Machine Learning and Generative AI solutions using Python.
• Build and optimize prompt engineering strategies for Large Language Model (LLM)-based applications.
• Develop document extraction, parsing, preprocessing, and chunking pipelines for structured and unstructured data.
• Train, evaluate, fine-tune, and monitor ML models for performance and accuracy.
• Manage data tagging, annotation, and labeling workflows to support model development.
• Implement embedding generation, semantic search, and retrieval-augmented generation (RAG) solutions.
• Integrate AI/ML models with Vector Databases and MongoDB for efficient data retrieval and storage.
• Collaborate with cross-functional teams to translate business requirements into AI-driven solutions.
• Ensure code quality, scalability, security, and production readiness of deployed solutions.
• Stay current with emerging trends and advancements in Artificial Intelligence, Machine Learning, and Generative AI technologies.

• Python, hands on experience in model training, document processing pipelines, and strong knowledge of vector databases and modern MLGenAI frameworks, * We are seeking a highly skilled Data Science Engineer to design, develop, and deploy scalable Machine Learning (ML) and Generative AI (GenAI) solutions.
• The ideal candidate will possess deep expertise in Python programming, model training, document processing pipelines, vector databases, and modern AI/ML frameworks. This role requires hands-on experience in building production-ready AI applications that leverage LLMs, embeddings, and intelligent document processing.

Must Have Skills

• Skill 1 - Python
• Skill 2 - Machine Learning Model Training & Evaluation
• Skill 3 - Generative AI / Large Language Models (LLMs)
• Skill 4 - Prompt Engineering
• Skill 5 - Document Extraction, Parsing & Chunking
• Skill 6 - Embeddings & Vector Search
• Skill 7 - Vector Databases
• Skill 8 - MongoDB
• Domain Experience (If any) - Data Science, Machine Learning, Generative AI, Intelligent Document Processing, * Bachelor's or Master's degree in Computer Science, Data Science, Artificial Intelligence, Machine Learning, or a related field.
• Expert-level proficiency in Python programming.
• Strong hands-on experience in Machine Learning model development, training, evaluation, and optimization.
• Experience with data tagging, annotation, and labeling workflows.
• Hands-on experience in document extraction, parsing, chunking, and intelligent document processing.
• Strong understanding of Machine Learning algorithms, statistical modeling, and Generative AI concepts.
• Experience working with Vector Databases (Pinecone, Weaviate, Chroma, FAISS, Milvus, etc.).
• Experience with MongoDB and NoSQL databases.
• Knowledge of embeddings, semantic search, and Retrieval-Augmented Generation (RAG) architectures.
• Experience building and deploying scalable AI applications in production environments., * Experience with LLM frameworks such as LangChain, LlamaIndex, or Semantic Kernel.
• Experience with cloud platforms such as AWS, Azure, or GCP.
• Familiarity with MLOps practices, CI/CD pipelines, and model monitoring tools.
• Experience with REST APIs and microservices architecture.
• Knowledge of Docker, Kubernetes, and containerized deployments.

Nice-to-Have Skills

• LangChain
• LlamaIndex
• Semantic Kernel
• MLOps
• AWS / Azure / GCP
• Docker & Kubernetes
• CI/CD Pipelines

Domain Experience

• Artificial Intelligence (AI)
• Machine Learning (ML)
• Generative AI
• Intelligent Document Processing (IDP)
• Data Science & Analytics

Experience

• 5+ Years of Data Science / Machine Learning Engineering Experience with 2+ Years in Generative AI Solutions Development.