AI/ML Engineer - Bangalore and Pune

Key Skills: AI/ML Engineer, Machine Learning Engineer, Data Scientist, AI Engineer, Applied Scientist.

• Python, TensorFlow, PyTorch, Scikit-learn, deep learning, NLP, computer vision, SQL, PostgreSQL, ETL, data pipelines, cloud (AWS, GCP, Azure), model deployment.
• Agentic AI, multi-agent, tool calling, LangChain, Google ADK, RAG pipelines.
• Good to have: Hadoop, Spark.

Key Responsibilities:

• Machine Learning Model Development: Research, design, and implement advanced machine learning algorithms and models to address business challenges.
• Data Engineering: Extract, transform, and load (ETL) large datasets from various sources into a Postgres database.
• Model Deployment: Deploy machine learning models into production environments, ensuring optimal performance and scalability.
• AI Integration: Integrate AI capabilities into existing systems and applications.
• Agentic AI / GenAI: Build and integrate agentic AI and RAG-based applications using Python and frameworks such as LangChain and Google ADK, including tool calling and multi-agent workflows.
• Document AI / IDP: Build and tune models for document classification, OCR post-processing, layout-aware key-value and table extraction, and LLM-based extraction, with confidence scoring and a human-in-the-loop feedback loop.
• Team Leadership: Mentor and guide junior team members in machine learning and data science practices.
• Problem Solving: Analyze complex business problems and develop innovative solutions using machine learning techniques.
• Collaboration: Work closely with cross-functional teams to understand business requirements and translate them into technical solutions

Required Skill Set:

Technical Skills:

• Machine Learning: Strong proficiency in machine learning algorithms (regression, classification, clustering, deep learning) and their implementation using Python libraries (TensorFlow, PyTorch, Scikit-learn).
• AI: Understanding of AI concepts, including natural language processing (NLP), computer vision, and reinforcement learning.
• Generative AI and Agentic AI: Hands-on experience with RAG, LangChain, Google ADK, and building agentic workflows (tool calling, multi-agent orchestration) in Python.
• Programming: Expert-level Python programming skills, including data manipulation, statistical analysis, and model development.
• Database: Proficiency in SQL and experience with PostgreSQL for data storage and retrieval.
• Cloud Platforms: Familiarity with cloud platforms (AWS, GCP, Azure) for deploying and managing machine learning workloads.
• Data Engineering: Experience with data pipelines, ETL processes, and data preprocessing techniques.
• Big Data: Knowledge of big data technologies (Hadoop, Spark) is a plus.
• IDP (good to have): Experience with OCR engines or cloud OCR services, document understanding models, LLM or vision-language based extraction, and extraction accuracy evaluation.

Soft Skills:

• Problem Solving: Ability to analyze complex problems and develop effective solutions.
• Communication: Excellent communication skills to explain technical concepts to both technical and non-technical audiences.
• Collaboration: Strong teamwork and interpersonal skills to work effectively with cross-functional teams.
• Leadership: Ability to mentor and guide junior team members.
• Business Acumen: Understanding of business objectives and how machine learning can drive business value.
• Continuous Learning: Passion for staying updated with the latest advancements in machine learning and AI.