{"id":198061,"url":"https://alion.io/job/terac-machine-learning-engineers-scenario-building-for-reinforcement-learning","title":"Machine Learning Engineers: Scenario Building for Reinforcement Learning","company":{"id":5329,"name":"Terac","domain":"terac.com","url":"https://alion.io/company/terac","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":75,"open_postings":7,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":31,"computed_at":"2026-10-31T05:58:55Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"contractor","work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"board_field","remote_working_hours":null,"hiring_geo_confidence":"structured","locations":[],"countries":[],"hiring_countries":["US"],"hiring_countries_total":1,"salary":null,"salary_estimate":{"min_usd":140000,"max_usd":311000,"period":"year","method":"role_country_seniority_unknown","sample_n":4425},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Machine Learning","optional":false},{"name":"Reinforcement Learning","optional":false}],"status":"live","first_seen_at":"2026-09-03T18:16:18Z","employer_posted_date":"2026-09-03","last_verified_at":"2026-10-31T09:56:39Z","board_verified":true,"closed_at":null,"days_open":57,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":57},"description":"What We're Researching\nWe're hiring AI researchers and machine learning engineers to participate in building worlds within a reinforcement learning platform. This work directly influences how agents interact with complex, simulated environments during their training cycles. Your technical expertise will help us refine the tools and interfaces used to create robust testing scenarios.\nHow It Works\nYou will connect to our remote platform to design and construct specific scenarios for reinforcement learning agents. Throughout the session, you will configure environmental parameters, define spatial constraints, and run preliminary agent interactions to test your setup. You will document your workflow and note any friction points encountered while structuring the environment. Finally, you will participate in an interview to share your feedback on the platform's overall usability.\nWho This Is For\nThis study targets professionals with hands-on experience in simulation design and reinforcement learning environments. We welcome machine learning engineers, AI researchers, simulation developers, and technical game designers accustomed to RL frameworks. Candidates should be highly comfortable configuring complex platform interfaces and defining structured agent scenarios.\nWhat You'll Do\nDesign and build specific scenarios within a remote reinforcement learning platform\n\nConfigure environmental parameters and define agent interaction rules\n\nTest initial agent behaviors to validate your scenario structure\n\nWalk us through your workflow and highlight areas for platform improvement\n\nWho Should Apply\nProfessional experience in machine learning or artificial intelligence research\n\nHands-on background in building simulations or reinforcement learning environments\n\nFamiliarity with configuring platform interfaces and defining reward structures\n\nComfortable articulating technical feedback during a remote interview\n\nCompensation\n$90 per hour\nReady to participate?\nStart your paid interview now\nAbout Terac\nTerac is building the world's largest pool of vetted human experts for AI. 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