Machine Learning Engineer

Role overview

What you will build

• Develop data movement pipelines, training and inference workflows, model-serving services, APIs, and evaluation frameworks.
• Support recommendation, forecasting, anomaly detection, classification, natural language processing, semantic search, and generative AI use cases.
• Perform feature engineering, experiment design, model tuning, and offline and online validation.
• Integrate models into scalable product architectures.
• Improve LLM workflows using prompt design, retrieval-augmented generation, vector search, guardrails, and response-quality evaluation.
• Implement CI/CD, monitoring, observability, testing, and model lifecycle automation for AI systems.
• Ensure solutions are reliable, cost-aware, secure, and ready for enterprise scale.

About you

• Have 1–3+ years of experience in machine learning engineering, software engineering, or a related field.
• Have a track record of deploying machine learning models into production.
• Build reliable and scalable machine learning systems and take ownership of end-to-end solutions.
• Balance experimentation with engineering rigor to make models innovative and production-ready.
• Work collaboratively as a problem-solver.