Machine learning engineer • glendale az
AI training project by creating reinforcement learning environments that evaluate AI models on complex software engineering tasks using.You will design reproducible environments, deterministic veri... Show more
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This is a contract, on-site role for a Java-Python Senior Engineer located in Phoenix, AZ.The Senior Engineer will be responsible for designing, developing, and maintaining software solutions using... Show more
AI Engineer - Agentic AI, Node Js<br /> <br /> Typescript and Python, Gen AI, Agentic AI.Client is not considering candidates who do not have experience on this.Technical Skills:<br ... Show more
Service Wire Company, a premier supplier of industrial and utility wire and cable, is currently seeking Machine Operators in Phoenix, AZ.If you are looking to join a great organization and a chance... Show more
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Graduate Medical Education Program Coordinator.Primary City/State: Phoenix, Arizona.Department Name: Medical Educ Admin-Hosp.Job Category: Administrative Services.We want to change the lives of tho... Show more
Assistant Math Learning Center Director.Benefits: 401(k), 401(k) matching, employee discounts, free food & snacks, paid time off.Why Work with Us: At Mathnasium of Mathnasium (ID: 2202501), we're p... Show more
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The average salary range is between $ 124,693 and $ 200,000 year , with the average salary hovering around $ 154,997 year .
Job Type: Contractor (~15 hours/week)
Location: Remote
We are seeking experienced Senior Software Engineers to support an AI training project by creating reinforcement learning environments that evaluate AI models on complex software engineering tasks using Model Context Protocol (MCP) tools.
You will design reproducible environments, deterministic verification, and reference solutions for tasks such as bug fixing, feature implementation, codebase refactoring, and performance optimization. No prior AI experience is required.
Compensation is output-based, with payment provided per task that meets project specifications. Minimum weekly submission requirements may apply.
Selected experts should be prepared to begin their first tasks within 24–48 hours of completing onboarding.
