Machine Learning Engineer

We’re looking for a Machine Learning Engineer with strong system design skills and sound ML and agentic engineering practices.

You'll be working on

• Build and maintain ML pipelines for feature generation, batch prediction and data publishing using Airflow and cloud data platforms.
• Develop high traffic model-serving APIs with clear contracts, appropriate caching and reliable handling of timeouts and failures.
• Package and deploy services using containers, Kubernetes and CI/CD. Maintain tests, logs and monitoring that help the team investigate problems.
• Work with Data Scientists to validate model releases and check the intended preprocessing and model behavior.
• Build and improve LLM-based applications and AI agents, including retrieval, MCP integration and agent definitions.
• Measure and improve service latency, throughput and infrastructure cost without compromising model quality or security.
• Partner with Product, Engineering, Data Science and Risk teams to define requirements, manage dependencies and deliver changes with rollout and rollback plans.

Qualifications

• 2-4 years of experience in machine learning engineering, MLOps, or software engineering with hands-on responsibility for ML systems.
• Strong programming and SQL skills, with experience writing maintainable code and working with Git, unit tests and code reviews. Experience in building maintainable, structured, and clean codebases with AI agents.
• Experience deploying or maintaining a model-serving API or a production ML pipeline.
• Working knowledge of Airflow, data partitioning, task dependencies and retry-safe processing.
• Familiarity with Docker or Podman, Kubernetes fundamentals and CI/CD workflows.
• Understanding of model evaluation, train/validation/test splits, data leakage and threshold selection. Experience with frameworks such as scikit-learn, PyTorch or TensorFlow.
• Familiarity with LLM and Agentic applications, retrieval or tool-calling agents, including the need of complex multi-agents workflow.
• Ability to explain technical tradeoffs, estimate effort and connect engineering decisions to business requirements and costs.
• A self-starter who takes ownership of delivery and communicates blockers early.
• Nice to have:
• Experience with Python, Rust, Go and API frameworks.
• Experience with Alibaba and Google Cloud products.
• Exposure to Triton Inference Server, TensorRT or GPU inference optimization.
• Experience with feature store, credit scoring, recommendation ranking, fraud detection, KYC, computer vision or geospatial features.
• Experience building MCP servers or operating AI agents.