Job Overview
This role is focused on developing and deploying machine learning models that power autonomous exception resolution, anomaly detection, and explainable insights. As an ML Engineer, you will work closely with multiple LLM ecosystems to implement retrieval-augmented generation pipelines, develop prompt engineering and safety techniques, and integrate memory and explainability into agentic workflows.
Key Responsibilities:
* Design, train, fine-tune, and deploy ML/LLM models for production use.
* Build RAG pipelines using vector databases and frameworks like LangChain, LangGraph, and MCP.
* Develop prompt engineering, optimization, and safety techniques for agentic LLM interactions.
* Collaborate with data engineering teams to maintain data pipelines for ML workloads.
* Conduct feature engineering and embeddings generation on structured and unstructured data.
* Implement model monitoring, drift detection, and retraining pipelines.
* Explore emerging LLM/SLM architectures and multi-agent orchestration patterns.
* Mentor junior engineers and contribute to best practices in ML engineering.
Required Qualifications:
The ideal candidate will have a Bachelor's or Master's degree in Computer Science, Data Science, Machine Learning, or a related field. They should also possess 3+ years of experience building and deploying ML systems, as well as strong Python skills and experience with PyTorch, TensorFlow, Scikit-Learn, Hugging Face Transformers.
A deep understanding of SQL and distributed data frameworks like Spark or Ray is also essential. Familiarity with at least two of the following LLMs/SLMs - OpenAI GPT, Anthropic Claude, Google Gemini, Meta LLaMA - is required, along with knowledge of vector databases, embeddings, and RAG pipelines.
Additionally, the candidate should have hands-on experience working with both structured and unstructured data at scale, as well as a solid understanding of the ML lifecycle - data preparation, training, evaluation, deployment, and monitoring.
Benefits
By joining this team, you will have the opportunity to work on cutting-edge projects, collaborate with experienced professionals, and grow your career in the field of machine learning engineering.