{"id":2090820,"url":"https://alion.io/job/mistral-ai-research-engineer-eval-platform","title":"Research Engineer - Eval Platform","company":{"id":22,"name":"Mistral AI","domain":"mistral.ai","url":"https://alion.io/company/mistral-ai","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":90,"open_postings":5,"ghost_share":0,"stale_share":0.2,"repost_share":0,"time_to_fill_p50_days":66,"computed_at":"2026-10-10T05:45:15Z"}},"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":["Paris, France"],"countries":["FR"],"hiring_countries":[],"hiring_countries_total":0,"salary":null,"salary_estimate":{"min_usd":54000,"max_usd":119000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":8},"experience_years_min":4,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"CI/CD","optional":false},{"name":"Kubernetes","optional":false},{"name":"LLM","optional":false},{"name":"Mistral","optional":false},{"name":"Python","optional":false},{"name":"Ray","optional":false},{"name":"SLURM","optional":false},{"name":"LLM Evaluation","optional":true},{"name":"SGLang","optional":true},{"name":"vLLM","optional":true}],"status":"live","first_seen_at":"2026-10-08T12:37:30Z","employer_posted_date":"2026-10-08","last_verified_at":"2026-10-11T16:02:29Z","board_verified":true,"closed_at":null,"days_open":3,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":3},"description":"About Mistral\nMistral provides full-stack AI solutions: from frontier models to developer tools, applications, and compute. We partner with enterprises tackling the hardest problems across high-stakes industries like finance, manufacturing, defense, healthcare, and the public sector, co-creating customized AI systems that they can run on their terms.\nWe are a dynamic, collaborative team passionate about AI and its potential to transform society. Our diverse workforce thrives in competitive environments and is committed to driving innovation. Our teams are distributed between Europe, North America, Asia and the Middle East. We are creative, low-ego and team-spirited.\nThe Role\nEvaluation is how we decide which models, checkpoints and recipes ship. As a Research Engineer on the Eval Platform team, you will build the infrastructure every science team relies on to measure model quality, and make it reliable, reproducible and fast.\nYou don't need to have designed benchmarks before. You do need to care about what a score means, and about when a difference between two runs is real.\nWhat you will do\nBuild systems that keep eval results reproducible and comparable over time, as models, benchmarks and code evolve.\n\nRun evaluations at scale across our GPU clusters, from model serving to scoring.\n\nMake eval results easy to access, explore and trust, through APIs and dashboards that researchers use every day.\n\nCatch broken or noisy evals before they mislead research decisions.\n\nSupport evaluation of agentic, multi-turn and tool-using models.\n\nWork closely with researchers to turn new evaluation needs into robust, shared tooling.\n\nWhat we're looking for\nMaster's or PhD in Computer Science, or equivalent experience.\n\n4+ years building production-grade software, ideally large-scale ML codebases or distributed systems.\n\nExcellent Python and strong software-design instincts: testing, code review, CI/CD.\n\nExperience running workloads on GPU clusters (Slurm, Kubernetes, Ray or similar).\n\nFamiliarity with LLM inference and evaluation.\n\nA product mindset: researchers are your users.\n\nSelf-starter, low-ego, collaborative.\n\nNice to have\nExperience building or maintaining evaluation harnesses or benchmarks.\n\nHands-on experience with inference engines such as vLLM or SGLang.\n\nExperience with agentic or RL environments.\n\nStatistics for experimentation: variance estimation, significance testing.\n\nOpen-source contributions to ML tooling.\n\nWhat We Offer\nWe offer a comprehensive benefits package designed to support your well-being, growth, and work-life balance. Benefits vary by country and may include healthcare coverage, parental leave, retirement plans, relocation support, wellness programs, meal and transportation allowances, and other location-specific perks.\nFor the most up-to-date details on benefits available in your location, please refer to our Benefits page.\nPrivacy Policy\nYour privacy matters to us. 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