5 junior machine learning engineer jobs at 5 companies in Chicago, IL
🚀PromotedHiringCafe
ML Engineer - Inference & Model Deployment
Cupertino, CA, US
$250k-$310k/yrOn-SiteFull Time
HiringCafe: Building a 100× better job search engine to take on Indeed and LinkedIn.
Turn powerful AI and ML models into fast, reliable production systems. Own inference latency, throughput, model-serving architecture, multi-GPU systems, and production deployment for millions of users.
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.
The HartfordNYSE: HIG: Provides business and personal insurance, group benefits, and investments.
1+ YOEMust be authorized to work in the U.S.; 1+ years research/DevOps experience; experience with AWS and/or GCP, CI/CD (Jenkins), IAC (CloudFormation/Terraform), Unix, git, Python, workflow automation (Airflow/Autosys), and MLOps practices.
Austin or Chicago or New York or Old Greenwich or San Francisco or West Palm Beach
$150k/yrOnsiteFull Time
WorldQuant: Develops systematic investment strategies through quantitative research and data.
Undergraduate or advanced degree in a quantitative field; programming in Python and/or C++; Linux experience; strong problem-solving and quantitative skills; interest in financial data, machine learning, and data engineering.
PayPalNASDAQ: PYPL: Global digital payments platform for consumers and merchants.
2+ YOEMaster's in Engineering/Statistics (or equivalent) plus 2 years experience; experience in payments/financial risk, Python, SQL, machine learning, A/B testing, and dashboarding with Tableau/Looker.
Data Scientist - Substation Engineering (Utilities)
Oakbrook Terrace, Illinois, United States
$74k-$102k/yrHybridFull Time
ExelonNASDAQ: EXC: Electric utility holding delivering energy to customers.
2+ YOEBachelor's degree in a quantitative field, 2+ years analyzing large datasets, strong knowledge of machine learning/statistics, experience with Python/SQL and Azure, Unix and big-data tools, and strong communication skills.
Microsoft Azure, Python, R, Scala, Spark, Hadoop, copilot, claude, Microsoft Power BI, SQL, Dask, Unix