Machine Learning Engineer

• Architect and implement multi agent systems capable of planning, tool use, and coordinated task execution.
• Design and optimize RAG pipelines including embeddings, hybrid retrieval, reranking, and context window strategies.
• Fine tune and evaluate small, medium, and large language models for domain specific reasoning and summarization.
• Develop prompt engineering frameworks, guardrails, and automated evaluation suites for agent reliability.
• Build scalable ML services and APIs for production deployment in distributed environments.
• Collaborate with product, engineering, and domain experts to translate complex workflows into agentic AI solutions.
• Establish best practices for model evaluation, observability, safety, and compliance.
• Mentor DS/ML engineers and contribute to long term AI strategy and architecture.
• 6–12+ years in Data Science / ML Engineering, with deep experience in LLM based systems.
• Proven experience building agentic architectures (planner executor, tool use agents, ReAct style reasoning).
• Strong background in RAG, embeddings, retrieval optimization, and evaluation.
• Expertise in NLP, transformers, deep learning, and model fine tuning.
• Proficiency with PyTorch, Hugging Face, Lang Chain/Llama Index, Ray, Kubernetes, and vector databases.
• Experience designing production grade ML systems with monitoring, evaluation, and observability.
• Strong communication skills and ability to lead technical direction.

Preferred Qualifications

• Experience in enterprise search, knowledge management, or high compliance domains.
• Experience with model distillation, LoRA/QLoRA, PEFT, and model compression.
• Experience building evaluation frameworks for hallucination, grounding, and agent reliability.
• Familiarity with knowledge graphs, symbolic reasoning, or hybrid neuro symbolic systems.
• Publications, patents, or open source contributions in LLMs or agent systems.
• Strong coding skills in Python 7+ years
• Be a natural problem solver, able to take a lead in collaborating to resolve issues
• Proficiency in IDE debugging : VSCODE and PYCHARM
• Have communication skills
• 5+ years of experience in AI and machine learning
• Deep understanding of machine learning algorithms, classification models, diagnostic testing of models
• Experience working directly and Transformer based architectures including BERT, RoBERTa, T5 etc. Nd familiarity with large language models and fine tuning
• Experience with conversational search / semantic search, reinforcement learning, prompt engineering, hallucination mitigation
• Working understanding of the business risks associated with applying LLM (Lang Chain) in a business
• Experience working with AWS, RAG, Sage Maker, SQL