{"id":2861043,"url":"https://alion.io/job/mistral-ai-evaluation-engineer-applied-ai","title":"Evaluation Engineer, Applied AI","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":95,"open_postings":196,"ghost_share":0,"stale_share":0.005,"repost_share":0,"time_to_fill_p50_days":64,"computed_at":"2026-10-28T05:59:10Z"}},"role":"Industrial Engineering","role_family":"Industrial Engineering","seniority":"junior","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":43000,"max_usd":66000,"period":"year","method":"role_seniority_country_remote_cell","sample_n":23},"experience_years_min":2,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"LLM","optional":false},{"name":"LLM Evaluation","optional":false},{"name":"Mistral","optional":false},{"name":"Post-training","optional":false},{"name":"Python","optional":false},{"name":"Synthetic Data","optional":false}],"status":"live","first_seen_at":"2026-10-19T15:41:16Z","employer_posted_date":"2026-10-19","last_verified_at":"2026-10-28T12:42:59Z","board_verified":true,"closed_at":null,"days_open":8,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":8},"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\nThis is a chance to build the frontier LLM evals that shape the next generations of flagship models.\nCould a model design a computer chip, or find the backdoor an attacker left in a network? Public benchmarks can't tell us, as they're generally not a good measure of real work.\nAs an Evaluation Engineer, you'll own evals from start to finish. You'll run workshops with customers, industry experts and our customer-facing teams to understand their most important industry use cases (e.g., an engineer updating a part in CAD software), and help decide which are worth building first. You'll also look beyond today's use cases and design moonshot evals for work no model can do yet, so Mistral gets there first. Then you'll turn each one into a benchmark, often one where an agent has to do the work inside real software. You'll source the data, decide how to score it, and run it on every new Mistral model and on competitor models.\nWhen our models fall short, you'll work with the post-training teams to close the gap. When they catch up, you'll make the eval harder. You'll write up and present your results so senior leaders can act on them. They also give our go-to-market teams evidence of where Mistral leads.\nYou'll learn new fields quickly. One month you might be learning how chip designers check their work, and the next how a bank investigates a flagged payment.\nThe team is new and fast-paced, and you'll have a lot of autonomy. You'll spend a lot of time speaking with people across Mistral to work out what matters most, then decide what to build.\nWhat You Will Do\nRun discovery with customers, industry experts and teams across Mistral, then help decide which use cases are worth building first.\n\nDesign new benchmarks for industry use cases and frontier capabilities, including how they're scored.\n\nBuild evals where agents work inside real software (e.g., CAD and simulation tools), and run them on our models with checks that the results stay reliable over time.\n\nStress-test existing evals to find flaws and bugs before we rely on them.\n\nSource data with expert vendors. Where customer data can't leave the customer, build realistic proxy or synthetic data instead.\n\nWrite up and present what you find so leaders across Mistral can act on it.\n\nHelp other teams build their own evals, with tools and guides they can reuse.\n\nWhat We're Looking For\nExperience\n2+ years of industry experience (e.g., in software, AI, or consulting), or a PhD.\n\nA software engineering or research background, with experience writing code that others can build on.\n\nExperience working directly with customers, industry experts, or other teams (e.g., through consulting, solutions engineering, or research collaborations).\n\nExperience building something with LLMs.\n\nComfort working with large datasets, including building and cleaning them.\n\nTechnical\nStrong Python skills.\n\nComfortable working in a large, shared codebase and getting your code through reviews by other teams.\n\nA strong understanding of LLM training, inference, and evaluation.\n\nCommunication\nYou enjoy speaking with people and are good at it.\n\nYou write clearly. A short doc or deck from you is enough for a busy leader to make a decision.\n\nConfident presenting to both technical and non-technical audiences.\n\nFluent in English.\n\nHow you work\nHigh energy, and you don't need a roadmap. You move independently and handle uncertainty with confidence.\n\nProactive and high-agency. You spot what needs doing and get it done.\n\nYou make good decisions about what to build first and can explain why.\n\nLow-ego, collaborative, and eager to learn.\n\nCurious, with a track record of learning things outside your work or studies. You can get to grips with a new field in a few weeks.\n\nNICE TO HAVE\nExperience building AI evaluations, especially for industry applications.\n\nPublished research on evals or contributions to open-source evaluation frameworks.\n\nExperience building datasets, generating synthetic data, developing labelling guidelines, or working with annotation vendors.\n\nA background in an industry outside software (e.g., engineering, finance, or science).\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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