{"id":2291329,"url":"https://alion.io/job/dna325-senior-machine-learning-engineer","title":"Senior Machine Learning Engineer","company":{"id":4411063,"name":"DNA325","domain":"dna325.com","url":"https://alion.io/company/dna325","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Manatal","truth_index":null},"role":"AI/ML","role_family":"AI/ML","seniority":"senior","employment_type":null,"work_mode":"remote","remote_scope":"stated_countries","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"explicit","locations":[],"countries":[],"hiring_countries":["DE","ID","IE","PL","ES","SE","CH","PT"],"hiring_countries_total":8,"salary":null,"salary_estimate":{"min_usd":104000,"max_usd":230000,"period":"year","method":"global_role_seniority_cell","sample_n":1986},"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"JAX","optional":true},{"name":"Python","optional":true},{"name":"PyTorch","optional":true}],"status":"live","first_seen_at":"2026-10-11T18:32:46Z","employer_posted_date":"2026-10-11","last_verified_at":"2026-10-13T01:28:53Z","board_verified":true,"closed_at":null,"days_open":1,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":1},"description":"Our client is an AI-native product company built to replace how billions of people manage their digital lives - starting with email, notes, and task tools that were never designed to be AI-native. It's backed by multi-million-dollar investment and built remote-first from day one, with a clear target: cut the time it takes users to get everyday things done by roughly 90%. That means solving the problems most AI products avoid - long-running workflows, persistent context, and reliable behavior under real-world, non-deterministic conditions. The team is small and high-talent-density by design, not by necessity, and moves at a pace that matches the scale of what it's building.\nAbout the Role\nIn this senior role, you're an independent owner of critical ML subsystems in production. You take ambiguous problems, design practical solutions, and ship systems that operate reliably at scale. This is a hands-on, high-impact role focused on depth.\nWhat You'll Work On\nBuild core ML systems that power a proactive, long-horizon AI product\nOwn work end-to-end: data preparation, training, evaluation, inference, iteration\nTurn research ideas into working systems that run reliably in production\nDebug model failures and system issues using real production signals\nIterate quickly: ship, measure outcomes, refine, repeat\nCollaborate closely with research, product, and engineering to deliver real user impact\nMentor and review work from other ML engineers through example and technical judgment\nWork under real production constraints: latency, cost, reliability, and safety\nRequirements\nYou've built and shipped ML systems used by real users\nYou understand how modern ML models behave - and misbehave - in production\nYou write strong, production-quality code and think in systems, not scripts\nYou take ownership, work independently, and push work across the finish line\nYou learn fast, communicate clearly, and improve through iteration\nLocation\nRemote, open to candidates in Poland, Portugal, Spain, Sweden, Switzerland, Germany, Ireland, Indonesia, Seoul, or Singapore.\nTech Stack\nPython · PyTorch / JAX · GPU-based training and inference systems\nWhat Success Looks Like\nML models and systems in production consistently meet accuracy, latency, reliability, and efficiency targets\nComplex production issues are monitored, debugged, and resolved with minimal disruption\nTraining, inference, and data pipelines are robust, scalable, and maintainable over time\nMeasurable improvements in ML systems driven by real-world signals and user feedback\nMentorship and technical guidance raise the overall ML engineering standard\nCross-functional collaboration ensures ML features integrate seamlessly into products and meet business goals\nWhat to Expect\nThe best products in the world are built by small, world-class teams. Decisions are made collectively, at rapid speed - balancing high-quality shipping with fast learning. You'll be expected to bring structure, exercise judgment, and execute independently.\nCompensation and benefits are competitive and vary by location; the package includes base salary and equity, discussed openly with you as part of the process.\nIf there's a fit, expect 3-4 interviews total, followed by a prompt, transparent decision. 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