Senior AI and Machine Learning Jobs

This list is updated hourly from a 20M+ job database and surfaces senior AI and machine learning roles across applied AI, ML engineering, generative AI, research, and production models.

Roles include senior, staff, or principal machine learning engineer, AI engineer, applied scientist, research scientist, ML platform engineer, AI architect, and engineering or research manager. Work may center on large language models, computer vision, natural language processing, recommendations, forecasting, model evaluation, inference systems, data and training infrastructure, or responsible-AI controls. A research lab may prioritize novel methods and publications, a product team may emphasize evaluation and user impact, and an ML platform group may own reliability, cost, deployment, and tools for other engineers. Seniority depends on technical originality, production or research ownership, the scale and risk of decisions, cross-team direction, and mentoring or management. Distinguish roles that train models from those integrating model APIs, and distinguish principal technical leadership from responsibility for hiring and team performance.

Place each role on a research-to-production spectrum before comparing its tool list. Confirm how much work involves model development, evaluation, software engineering, data or training infrastructure, deployment, and ongoing operations. Ask who defines evaluation criteria, owns model behavior after release, and decides when a system is ready for use. The original posting should also clarify model families and frameworks, cloud stack, publication or advanced-degree expectations, safety responsibilities, and on-call terms. A stated selection process may involve coding, ML system design, statistics, a research presentation, or evaluation work; use the description to prioritize preparation. Company, location, compensation, and sponsorship filters handle practical constraints. Weigh disclosed compensation and equity against company stage, compute and data resources, research freedom, technical scope, and management expectations.

Browsing does not require an account. A free account adds saved AI and machine-learning roles, application tracking, and Copilot. Keep the research-to-production balance in your notes and recheck the source before applying.