5 machine learning platform engineer jobs at 5 companies in Illinois
🚀PromotedHiringCafe
Founding Machine Learning / AI Search Engineer
Cupertino, CA, US
$160k-$310k/yrOn-SiteFull Time
HiringCafe: Building a 100× better job search engine to take on Indeed and LinkedIn.
Build the ML and AI search behind HiringCafe — ranking, recommenders, retrieval, and LLM agents that surface jobs people would never find on their own.
HiringCafe: Building a 100× better job search engine to take on Indeed and LinkedIn.
Own the crawlers, pipelines, and infrastructure powering a real-time job search engine. Strong Node.js and Python fundamentals; bonus points for security and reverse-engineering chops.
TransUnionNYSE: TRU: Provides global credit reporting and risk management information solutions.
5+ YOEML platform design and development; R/Python/SQL; Spark; HPC workflows; advanced degree or 5+ years quantitative experience; leadership in ML projects.
Thoughtworks: Global consultancy providing software engineering and digital strategy services.
Proven ML engineering experience designing scalable ML systems, strong Python coding, experience with distributed systems, MLOps/CI/CD, and cloud platforms (Azure/AWS/GCP/Databricks); stakeholder management and leadership skills.
Arizona or California or Colorado or Florida or Georgia or Illinois or Indiana or Massachusetts or Michigan or Minnesota or Missouri or New Jersey or New York or North Carolina or Ohio or Pennsylvania or Texas or Wisconsin
$101k-$168k/yrRemoteFull Time
SullivanCotter: Consulting and data for healthcare and nonprofit compensation strategies.
3+ YOEBachelor's or Master's in CS/Data Science/Statistics/Math (or related experience). 3+ years relevant experience (Master's) or 5+ years (Bachelor's). Proficient in Python, ML/LLM architectures, RAG pipelines, ML libraries, cloud platforms, MLflow and Git.
Shirley Ryan AbilityLab: Provides inpatient rehabilitation care and clinical research services.
3+ YOE3+ years in ML/AI engineering; proficient in Python; experience deploying/operationalizing ML models; strong Git; knowledge of Docker/Kubernetes; cloud platforms (Azure/AWS/GCP); strong problem-solving and communication.
Git, Docker, Kubernetes, Azure, AWS, Google Cloud, Python, Linux, Windows