Machine Learning Engineer

Role: ML Principle EngineerLocation: RemoteJob DescriptionCore ResponsibilitiesArchitect 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.Expertise Desired6–12+ 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, HuggingFace, LangChain/LlamaIndex, 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 QualificationsExperience 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+ yearsBe a natural problem solver, able to take a lead in collaborating to resolve issuesProficiency in IDE debugging : VSCODE and PYCHARMHave communication skills5+ years of experience in AI and machine learningDeep understanding of machine learning algorithms, classification models, diagnostic testing of modelsExperience working directly and Transformer based architectures including BERT, RoBERTa, T5 etc. Nd familiarity with large language models and fine tuningExperience with conversational search / semantic search, reinforcement learning, prompt engineering, hallucination mitigationWorking understanding of the business risks associated with applying LLM (LangChain) in a businessExperience working with AWS, RAG, SageMaker, SQL