{"id":4180603,"url":"https://alion.io/job/clera-full-stack-software-engineer-reinforcement-learning-7","title":"Full-Stack Software Engineer, Reinforcement Learning","company":{"id":2706,"name":"Clera","domain":"getclera.com","url":"https://alion.io/company/clera","size_band":"11-50","is_staffing_agency":true,"employer_type":"agency","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":80,"open_postings":40,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":6,"computed_at":"2026-11-12T10:38:37Z"}},"role":"Backend","role_family":"Backend","seniority":"middle","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":130000,"max":225000,"currency":"USD","period":"year","gross":null,"usd_annual":225000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":true,"relocation_package":true,"has_equity":false,"technologies":[{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Docker","optional":false},{"name":"Grafana","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Next.js","optional":false},{"name":"Python","optional":false},{"name":"React.js","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Terraform","optional":false},{"name":"TypeScript","optional":false},{"name":"JavaScript","optional":true}],"status":"live","first_seen_at":"2026-11-12T17:05:21Z","employer_posted_date":"2026-11-12","last_verified_at":"2026-11-12T17:22:33Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About the Role\nBuild product interfaces, backend systems, and internal tools for a reinforcement learning data platform. You will own experiences that help research teams and external partners create, evaluate, and improve training data, working closely with research, operations, and go-to-market teams.\nWhat You'll Do\nDevelop tools for browsing environments, inspecting trajectories, reviewing task quality, and understanding model behavior.\n\nBuild partner workflows for creating, submitting, testing, and iterating on reinforcement learning environments and training data.\n\nCreate dashboards and observability tools for environment quality, evaluation results, data collection progress, and pipeline health.\n\nDesign backend services and APIs that connect task authoring, data collection, evaluation, quality assurance, and training infrastructure.\n\nWork with cross-functional teams to turn ambiguous needs into polished products and ship improvements quickly.\n\nWhat We're Looking For\nAt least 3 years of full-stack engineering experience building and shipping production systems, with technical field study or equivalent technical fundamentals.\n\nProficiency in Python and a modern web stack such as React, TypeScript, or Next.js.\n\nHands-on experience with AI, machine learning, or reinforcement learning, and experience owning products from design through deployment.\n\nExperience building backend services, APIs, and databases, as well as dashboards, monitoring tools, or observability interfaces.\n\nComfort with cloud infrastructure, Docker, CI/CD, and production debugging.\n\nExperience with data inspection, review, quality assessment, data collection, labeling, or evaluation tools is valuable. 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