{"id":2869320,"url":"https://alion.io/job/clera-aiml-engineer-individual-contributor","title":"AI/ML Engineer, Individual Contributor","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":30,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":6,"computed_at":"2026-10-25T05:49:26Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":["San Francisco, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":120000,"max":200000,"currency":"USD","period":"year","gross":null,"usd_annual":200000},"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Embeddings","optional":false},{"name":"LLM","optional":false}],"status":"closed","first_seen_at":"2026-10-19T17:04:00Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-10-25T20:59:07Z","board_verified":false,"closed_at":"2026-10-25T20:59:07Z","days_open":6,"trust":{"level":"not_scored","repost_count":null,"flags":[],"days_open":6},"description":"About the Role\nJoin an AI/ML team building tools to identify and address failures in production AI agents. This role owns the intelligence behind failure detection, evaluation, and proposed fixes, helping make agents more reliable for real-world use.\nWhat You'll Do\nDetect subtle agent failures, including omissions, incorrect responses, and patterns across large volumes of traces.\n\nTurn user behavior such as rephrasing, abandonment, and retries into evidence of potential failures.\n\nBuild evaluation methods that measure detection quality, including in situations without ground-truth labels.\n\nVerify that proposed fixes reproduce and resolve failures, and avoid recommending changes when evidence is weak.\n\nImprove the cost efficiency of detection by choosing appropriate models and methods for each task.\n\nReview production traces regularly to identify problems and guide product improvements.\n\nWhat We're Looking For\nDemonstrated AI/ML engineering experience, with 0 to 10 years of experience considered.\n\nExperience shipping products that people use and working as an individual-contributor engineer.\n\nHands-on experience with LLMs in production, including evaluations, LLM-as-judge, embeddings, and deciding when to use smaller models or no model.\n\nExperience running AI agents in production and handling their failures.\n\nStrong research judgment and the ability to distinguish meaningful improvements from noise, including when direct ground truth is unavailable.\n\nCompensation & Benefits\nBase salary range: $120,000 to $200,000 annually. Visa sponsorship is not available. 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