Machine Learning Engineer

4 days ago

Nashik, India EXL Full time

Key Responsibilities: - Design and implement modular, reusable AI agents capable of autonomous decision-making using LLMs, APIs, and tools like LangChain, AutoGen, or Semantic Kernel. - Engineer prompt strategies for task-specific agent workflows (e.g., document classification, summarization, labeling, sentiment detection). - Integrate ML models (NLP, CV, RL) into agent behavior pipelines to support inference, learning, and feedback loops. - Contribute to multi-agent orchestration logic including task delegation, tool selection, message passing, and memory/state management. - Collaborate with MLOps, data engineering, and product teams to deploy agents at scale in production environments. - Develop and maintain agent evaluations, unit tests, and automated quality checks for reliability and interpretability. - Monitor and refine agent performance using logging, observability tools, and feedback signals. Required Qualifications: - Bachelor's or Master's in Computer Science, AI/ML, Data Science, or related field. - 3+ years of experience in developing AI/ML systems; 1+ year in agent-based architectures or LLM-enabled automation. - Proficiency in Python and ML libraries (PyTorch, TensorFlow, scikit-learn). - Experience with LLM frameworks (LangChain, AutoGen, OpenAI, Anthropic, Hugging Face Transformers). - Strong grasp of NLP, prompt engineering, reinforcement learning, and decision systems. - Knowledge of cloud environments (AWS, Azure, GCP) and CI/CD for AI systems. Preferred Skills: - Familiarity with multi-agent frameworks and agent orchestration design patterns. - Experience in building autonomous AI applications for data governance, annotation, or knowledge extraction. - Background in human-in-the-loop systems, active learning, or interactive AI workflows. - Understanding of vector databases (e.g., FAISS, Pinecone) and semantic search. Why Join Us: - Work at the forefront of AI orchestration and intelligent agents. - Collaborate with a high-performing team driving innovation in enterprise AI platforms. - Opportunity to shape the future of AI-based automation in real-world domains like healthcare, finance, and unstructured data.

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