Sr Machine Learning Engineer

Overview

Senior Machine Learning Engineer to build and scale end-to-end machine-learning and generative-AI platforms, spanning core services, infrastructure, and governance controls.

What you'll do

• Engineer end-to-end ML pipelines from data ingestion through automated promotion.
• Harden research code into production micro-services and expose secure APIs.
• Build full-stack AI applications by integrating model services with UI/workflow layers.
• Optimize model performance and cost at scale to meet SLA targets.
• Implement observability for metrics, tracing, drift/bias detection, and analytics.
• Embed security and responsible-AI controls in partnership with Security/Privacy/Compliance.
• Contribute reusable platform components and support platform best practices.

What you'll need

• 3-5 years of experience in AI/ML and enterprise software.
• Command of ML algorithms including regression, ensembles, clustering, dimensionality reduction, time-series, deep learning, and LLM/RAG techniques.
• Experience selecting and integrating AI SaaS/PaaS offerings and building custom ML services at scale.
• Expert knowledge of GenAI tooling such as vector databases, RAG pipelines, prompt-engineering DSLs, and agent frameworks (e.g., LangChain, Semantic Kernel).
• Proficiency in Python and Java.
• Containerization skills using Docker/Kubernetes and cloud experience with AWS, Azure, or GCP.
• Knowledge of DevOps/MLOps tools including GitHub Actions and Bedrock/SageMaker Pipelines.