Sr Machine Learning Engineer
Core
Senior individual-contributor authority on building and scaling end-to-end machine-learning and generative-AI platforms, designing core services, infrastructure, and governance controls for hundreds of practitioners to prototype, deploy, and monitor models securely and cost-effectively.
Role type
Senior IC machine learning engineer (GenAI/MLOps platform)
Builds
Enterprise-grade AI developer experience, end-to-end ML pipelines, production-grade micro-services, full-stack AI applications, and reusable platform components (feature stores, model registries).
Domain
Healthcare technology / Biotechnology / Enterprise AI
Deliverable
production ML models | infrastructure | product features
Required skills
Machine learning algorithms (regression, tree-based ensembles, deep learning, LLMs/RAG), Python, Java, Docker/Kubernetes, Cloud platforms (AWS/Azure/GCP), DevOps/MLOps tools (Kubeflow, SageMaker Pipelines, GitHub Actions), Vector databases, RAG pipelines, Prompt-engineering DSLs, Agent frameworks (LangChain, Semantic Kernel), Business case modeling (TCO vs NPV), Stakeholder management.
Preferred skills
Biotechnology or pharma industry experience, Published thought leadership on enterprise GenAI, Master's degree in CS/Data Science, Agile/SAFe methodologies.
Technologies
Kubeflow, SageMaker Pipelines, Open AI SDK, Docker, Kubernetes, AWS, Azure, GCP, GitHub Actions, Bedrock, LangChain, Semantic Kernel, REST, gRPC.
Responsibilities
Engineer end-to-end ML pipelines (ingestion, feature engineering, training, optimization, evaluation, registration, automated promotion); Harden research code into production-grade micro-services with secure APIs; Build and maintain full-stack AI applications integrating model services with UI/workflow engines; Optimize performance and cost at scale using algorithm selection and resource tuning; Instrument comprehensive observability (metrics, tracing, drift/bias detection); Embed security and responsible-AI controls; Contribute reusable platform components and evangelize best practices; Perform exploratory data analysis and feature ideation; Partner with data scientists to prototype algorithms and benchmark scalability.
Seniority
Senior, hands-on IC
