Machine Learning Engineer

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.