{"id":3927127,"url":"https://alion.io/job/clera-founding-machine-learning-engineer-12","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":39,"ghost_share":0,"stale_share":1,"repost_share":0,"time_to_fill_p50_days":6,"computed_at":"2026-11-07T05:47:08Z"}},"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":"Machine Learning","optional":false},{"name":"Post-training","optional":false},{"name":"Python","optional":false},{"name":"Reinforcement Learning","optional":false}],"status":"live","first_seen_at":"2026-11-07T17:14:28Z","employer_posted_date":"2026-11-07","last_verified_at":"2026-11-07T20:25:37Z","board_verified":true,"closed_at":null,"days_open":0,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":0},"description":"About the Role\nOwn the machine learning function at an early-stage AI company, shaping post-training and agent systems from research through production. You will help set technical priorities and build the foundations for the ML team as it grows.\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 for trajectory and data quality.\n\nSet priorities for ML systems, experiments, and hiring, and lead technical direction as the team scales.\n\nWhat We're Looking For\nAt least 3 years of professional experience building or delivering production machine learning systems.\n\nHands-on experience with post-training ML, evaluation frameworks, and post-training data pipelines, including structuring, filtering, and scoring training data.\n\nStrong Python and systems-level software engineering skills for ML infrastructure.\n\nExperience with agents, reinforcement learning, trajectory data, reward structures, and agent environment design.\n\nExperience building evaluation benchmarks, replay and debugging tools, data validation, provenance tracking, or observability systems.\n\nAbility to bridge research and production, take ownership, and work effectively in an ambiguous, fast-moving environment.\n\nCompensation & Benefits\nSalary range: $100,000 to $250,000 USD annually. 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