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Machine Learning Platform Engineer
- Chicago, Illinois, United States
- Chicago, Illinois, United States
About
Responsibilities
Design and build internal ML platform services for model training, serving, and monitoring
Develop self-service tools enabling data scientists to deploy models without DevOps expertise
Build and maintain feature stores for consistent feature computation across training and serving
Implement experiment tracking, model registry, and artifact management systems
Optimize GPU resource scheduling and cost management for training workloads
Define platform SLAs and ensure high availability of ML infrastructure services
Requirements
5+ years of software engineering with 2+ years in ML platform or infrastructure roles
Strong experience with Kubernetes, Helm, and container orchestration at scale
Proficiency in Python and Go or Rust for building platform services
Experience with ML workflow orchestrators (Kubeflow, Airflow, Flyte, or Metaflow)
Knowledge of distributed computing frameworks (Ray, Spark, or Dask)
Experience with cloud infrastructure (AWS, GCP, or Azure) and infrastructure-as-code
Nice to Have
Experience building developer platforms or internal tooling
Knowledge of LLM serving infrastructure and GPU optimization
Familiarity with Feast, Tecton, or similar feature platforms
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Languages
- English
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