Machine Learning Engineer
Core
Design, build, and deploy end-to-end ML solutions (forecasting, agentic AI, operational models) for Fortune 500 clients in Financial Services, Manufacturing, and Energy.
Role type
Machine Learning Engineer
Builds
Production ML systems, APIs, and intelligent workflows for commercial enterprises
Domain
Commercial Digital (Financial Services, Manufacturing, Energy & Utilities)
Deliverable
production ML models
Required skills
End-to-end ML solution design, data pipelines, feature engineering, model training, time-series forecasting, NLP, LLM applications, RAG architectures, agent-based systems, API development (FastAPI/Flask), MLOps (CI/CD, monitoring, drift detection), client collaboration
Technologies
Agent Framework, LangChain, LangGraph, FastAPI, Flask
Responsibilities
Design and build end-to-end ML solutions from data pipelines to production deployment; Develop traditional ML and generative AI systems; Build financial and operational models; Create production-grade APIs and services; Implement MLOps practices; Collaborate directly with clients to understand business problems and translate requirements into technical solutions
Seniority
Mid-level (2+ years) to Senior Associate (3+ years)
