AI / ML Developer
Role details
Job location
Tech stack
Job description
AI / ML Developer (Senior) with skills AI/ML Development, Natural Language Processing (NLP), Large Language Models (LLM), Retrieval-Augmented Generation (RAG), Language Model Evaluation, Pre-trained Language Models, Fine-tuning Language Models, Knowledge Graph Embeddings, Zero/Few-shot Learning, Agent Memory, Multi-Agent Design, Agent Observability Tools, LangSmith, LangChain Agents, LangGraph, LangFlow, Vector DB Integration for location Bangalore, India, Infogain is seeking a motivated and innovative Junior AI Engineers/Data Scientists with a specialization in Generative AI. The ideal candidate will be enthusiastic about exploring new problems, driving innovation, and leveraging advanced machine learning techniques and programming skills (especially in Python). You will assist in developing and enhancing our generative ai based flagship solution and contribute to advancing our knowledge discovery solutions. This role is perfect for someone who enjoys learning, creative problem-solving, and working in a dynamic environment., * Requirement Gathering:
- Translate business requirements into actionable plans in collaboration with the team.
- Ensure alignment of plans with the customer's strategic objectives.
- Technical Approach
- Identify the right functional partitioning for the agentic solution
- Identify data sources and external connectivity needed for the solution to meet the business requirements
- Explore, diagnose, and resolve data discrepancies including ETL tasks, missing values, and outliers
- Define approaches for knowledge base construction and constructions. Prototype and benchmark if needed to arrive at the right approach
- Identify guardrails to ensure compliance with customer's organization policies and AI safety guidelines
- Define approaches to evaluate the performance of the solution with respect
- Development and Execution:
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Individually deliver projects, proof-of-concept (POC) initiatives from inception to completion.
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Contribute to the development and refinement of technical and agentic architecture, ensuring it aligns with project and organizational goals.
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Implement scalable and robust solution to support the business requirement
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Coordinating with cross-functional teams to achieve project goals.
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Delivery of production-ready models and solutions, meeting quality and performance standards.
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Monitor success metrics to ensure high-quality output and make necessary adjustments.
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Create and maintain documentation/reports.
- Innovation and Best Practices:
- Stay informed about new trends in Generative AI and integrate relevant advancements into our solutions.
- Implement novel applications of Generative AI algorithms and techniques in Python.
Requirements
- Bachelor's degree in computer science or a related field
- 2-6 years of experience in AI/ML, especially generative AI
- Proficiency in programming languages such as Python.
- Experience with Generative AI techniques and tools.
- Familiarity with ETL methods, data imputation, data cleaning, and outlier handling.
- Familiarity with cloud platforms (AWS, Azure, GCP) and AI/ML services.
Technical Skills - Desirable:
- Expertise in NLP and Generative AI concepts/methods/techniques like
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Prompt design/engineering
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Retrieval Augmented Generation (RAG), Corrective RAG and Knowledge Graph-based RAG using GPT-4o
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Fine-tuning through LORA/QLORA
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Multi-agentic frameworks for RAG
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Reranker etc. for enhancing the plain-vanilla RAG
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Evaluation frameworks like G-Eval etc.
- Experience in using python to build REST services using frameworks such as fastAPI.
- Experience in construction of knowledge graph with unstructured data, * Primary Skill: AI/ML Development
- Sub Skill(s): AI/ML Development
- Additional Skill(s): Natural Language Processing (NLP), Large Language Models (LLM), Retrieval-Augmented Generation (RAG), Language Model Evaluation, Pre-trained Language Models, Fine-tuning Language Models, Knowledge Graph Embeddings, Zero/Few-shot Learning, Agent Memory, Multi-Agent Design, Agent Observability Tools, LangSmith, LangChain Agents, LangGraph, LangFlow, Vector DB Integration, Experience in AI/ML Development Additional Skill(s) Natural Language Processing (NLP) Large Language Models (LLM) Retrieval-Augmented Generation (RAG) Language Model Evaluation Pre-trained Language Models Fine-tuning Language Models Knowledge Graph Embeddings Zero/Few-shot Learning Agent Memory
