About the Role :

We are looking for a hands-on AI/ML (GenAI) Engineer with experience in building, fine-tuning, evaluating, and deploying LLM-powered systems. The role involves working on LLM training and evaluation pipelines, Agentic AI systems, RAG architectures, vector search, and offline/on-premise AI deployments.

Key Responsibilities :

LLM Training & Evaluation :

- Build pipelines for SFT (Supervised Fine-Tuning), DPO (Direct Preference Optimization), and evaluation benchmarking.
- Develop automated evaluation frameworks and test harnesses.
- Perform regression testing and diagnose model issues.

Agentic AI System Development :

- Design agent workflows, planning loops, tool usage, and memory systems.
- Develop multi-step reasoning and AI automation systems.
- Implement prompt engineering and evaluation strategies.

RAG & Vector Search :

- Design and develop RAG pipelines, including ingestion, chunking, and embeddings.
- Work with vector databases such as Pinecone, Weaviate, and Milvus.
- Improve retrieval performance using reranking and evaluation techniques.

Deployment & Engineering :

- Deploy AI/ML systems in offline and on-premise environments.
- Build scalable APIs and services.
- Implement monitoring, logging, debugging,



and fallback mechanisms.

Collaboration :

- Collaborate with data scientists and ML engineers.
- Translate business requirements into practical AI solutions.
- Document systems, experiments, and technical implementations.

Required Qualifications :

- Bachelor's degree in Computer Science or a related field.
- 1.5 - 2 years of experience in AI/ML.
- Strong programming skills in Python.
- Hands-on experience with PyTorch, TensorFlow, or JAX.
- Experience with LLM fine-tuning and prompt engineering.

Must-Have Skills :

- Experience building Agentic AI systems and reasoning workflows.
- LangChain, LlamaIndex, LangGraph.
- Strong understanding of RAG.
- Experience building LLM evaluation pipelines.
- Understanding of Transformer models and embeddings.
- Experience deploying solutions in offline/on-premise environments.
- Familiarity with Vector Databases.
- Solid debugging and problem-solving skills.

Why Join :

- Work on advanced LLM and Generative AI systems.
- Build real-world AI solutions.
- Gain hands-on exposure to RAG, LLM evaluation, Agentic AI, and AI deployment.
- Work on challenging AI/ML engineering problems.

📌 McLaren Strategic Solutions - AI/ML Engineer - GenAI (India)
🏢 MCLAREN STRATEGIC VENTURES INDIA PRIVATE
📍 India