{"id":2641909,"url":"https://alion.io/job/clera-founding-machine-learning-engineer-9","title":"Founding Machine Learning Engineer","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":"2026-10-15T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","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":["Munich, Germany"],"countries":["DE"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":100000,"max":250000,"currency":"USD","period":"year","gross":null,"usd_annual":250000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":true,"relocation_package":false,"has_equity":false,"technologies":[{"name":"Function Calling","optional":false},{"name":"Machine Learning","optional":false},{"name":"Post-training","optional":false},{"name":"Python","optional":false},{"name":"Reinforcement Learning","optional":false},{"name":"Tool Use","optional":false}],"status":"live","first_seen_at":"2026-10-15T17:16:43Z","employer_posted_date":"2026-10-15","last_verified_at":"2026-10-15T22:42:30Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About the Role\nAn early-stage AI systems company is seeking a Founding Machine Learning Engineer to build its machine learning function and shape the technical direction of post-training and agent systems. You will work closely with the founding team and help set priorities for experiments, infrastructure, and future team growth.\nWhat You'll Do\nStructure, filter, and score experimental trajectories for training data pipelines.\n\nDesign and implement evaluations and benchmarks for model reasoning, planning, and experimental progress.\n\nBuild reliable agent environments, tool interfaces, observability systems, and replay infrastructure.\n\nEstablish validation and provenance tracking to improve trajectory and data quality.\n\nSet machine learning roadmap priorities across systems, experiments, and hiring.\n\nGuide the technical direction of the machine learning team as it grows.\n\nWhat We're Looking For\nAt least 3 years of experience in machine learning engineering, building or delivering production machine learning systems.\n\nProduction software engineering experience with Python and systems-level programming for machine learning infrastructure.\n\nHands-on experience with post-training machine learning, evaluation frameworks, and training data pipelines, including structuring, filtering, and scoring data.\n\nStrong understanding of trajectory data, reward structures, tool use, and agent environment design.\n\nExperience building agent environments, reinforcement learning systems, replay tools, or trajectory debugging infrastructure is valuable.\n\nAbility to connect research with production, take ownership, and work effectively in an ambiguous environment.\n\nCompensation & Benefits\nAnnual base salary: $100,000 to $250,000 USD. 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