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Back to all positions
AI & Machine LearningFull-timeHybrid

Machine Learning Platform Engineer

Build and scale the internal ML platform at APPIT Software in Chicago, creating self-service tools for model training, experiment tracking, feature management, and production deployment at enterprise scale.

Chicago, USA
Full-time
AI & Machine Learning

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

Skills

PythonKubernetesGoKubeflowRayFeature StoresTerraformPlatform Engineering

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