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Machine Learning Jobs in Usa
35 open positions · Updated 3 days ago
35 Machine Learning roles across 7 companies, most in AI/ML; 11% fully remote; typical advertised salary $185.8k
Who is hiring (7 companies)
Role types
Work arrangement: 4 fully remote · 6 hybrid · 3 on-site · 22 not stated
Advertised salaries: p25 $166.4k · median $185.8k · p75 $231k (from 10 disclosed annual salaries, USD)
Counts are open roles Joblaze currently tracks on company career pages for this exact skill/location; salaries are advertised minimums, annual, converted to USD.
Showing 20 of 35 positions
Search with filters →Join Waymo as a Summer Intern to work on ML frameworks and efficiency in a cutting-edge software engineering role.
Intern in machine learning focusing on driver refinement foundations at Waymo in San Francisco.
Join Waymo as a Summer Intern in Machine Learning, focusing on Planning and Prediction.
Join Waymo as a Summer Intern in Machine Learning, focusing on Planning and Prediction.
Join Waymo as a Summer Intern to work on ML systems and behavior discovery.
Lead an engineering team focused on building scalable anomaly detection systems using AI and machine learning.
Join Waymo as a Summer Intern focusing on Machine Learning in Driver Refinement Foundations.
Join Waymo as a Summer Intern in Machine Learning Research for 2027.
Join Waymo as a Summer Intern focusing on Perception and Machine Learning for the 2027 program.
Join Waymo as a Summer Intern in Software Engineering focusing on Systems Intelligence and Machine Learning.
Join Waymo as a Summer Intern in Software Engineering focusing on Systems Intelligence and Machine Learning.
Join Waymo as a Summer Intern to work on software engineering for simulation evaluation of ML models.
Join Waymo as a Summer Intern to work on software and machine learning engineering in simulation.
Join Waymo as a Summer Intern focusing on Machine Learning Engineering in San Francisco.
Join Abnormal Security as a Senior Software Engineer to build advanced systems for detecting email and cloud-based attacks.
Build foundational ML infrastructure for fraud detection and user personalization at a remote-first company.