{"id":122440,"url":"https://alion.io/job/sardine-machine-learning-engineer-2","title":"Machine Learning Engineer","company":{"id":5952,"name":"Sardine","domain":"sardine.ai","url":"https://alion.io/company/sardine","size_band":"201-500","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"B","score":83,"open_postings":6,"ghost_share":0,"stale_share":0.667,"repost_share":0,"time_to_fill_p50_days":56,"computed_at":"2026-11-03T05:54:40Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":null,"employment_type":"full_time","work_mode":"remote","remote_scope":"stated_regions","remote_scope_basis":"posting_text","remote_working_hours":null,"hiring_geo_confidence":"inferred","locations":[],"countries":[],"hiring_countries":["US","CA","MX","AI","AG","AW","BS","BB","BZ","BM","VG","BQ","KY","CR","CW","DM","DO","SV","GL","GD","GP","GT","HT","HN","JM","MQ","MS","NI","PA","PR","KN","LC","VC","PM","SX","TT","TC","VI"],"hiring_countries_total":38,"salary":null,"salary_estimate":null,"experience_years_min":null,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"CI/CD","optional":false},{"name":"GCP","optional":false},{"name":"Go","optional":false},{"name":"Kubernetes","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Docker","optional":true}],"status":"live","first_seen_at":"2025-09-09T00:09:30Z","employer_posted_date":"2025-09-09","last_verified_at":"2026-11-03T21:46:30Z","board_verified":true,"closed_at":null,"days_open":421,"trust":{"level":"stale","repost_count":0,"flags":["stale"],"days_open":420},"description":"Who we are:\nSardine is the leading agentic risk platform for fighting financial crime. Our integrated solution unifies data across risk teams to help organizations stop fraud in real time, prevent AI-driven attacks, and automate fraud and AML operations. Sardine’s platform is strengthened by one of the fastest-growing fraud consortiums in the market, spanning more than 6 billion profiled devices, 800 million consumers, and 3 million businesses worldwide. Leading companies including FIS, GoDaddy, Intuit, Edward Jones, ZoomInfo, and Checkout.com rely on Sardine to secure and grow trust in their products.\nOur culture:\nWe hire talented, self-motivated individuals with extreme ownership and high growth orientation.\n\nWe value performance and not hours worked. We believe you shouldn't have to miss your family dinner, your kid's school play, friends get-together, or doctor's appointments for the sake of adhering to an arbitrary work schedule.\n\nWe're a remote-first team spread across time zones, so no office to report to - work from wherever helps you do your best work. Just a couple of things to keep in mind: pay is based on where you're located, and you'll need to keep a home base in the country you're hired in. So while we love the \"coffee shop today, mountains tomorrow\" life, this isn't a passport-optional, work-from-anywhere-on-Earth kind of remote - think flexible within your country, not borderless.\n\nLocation:\nRemote - United States or Canada\n\nAbout the role:\nAs a Machine Learning Engineer at Sardine, you'll own the systems that make real-time fraud detection possible. Our data science team builds custom models for our clients, you build and run the platform they deploy onto, and the low-latency serving path those models score on.\nSardine scores millions of sessions in real time from hundreds of device and behavioural signals, inside a sub-250ms budget. That constraint shapes everything: how features are computed and served, how models are deployed and rolled back, how quickly you know when something has degraded. You'll be the person who figures out why a model broke.\nWhat you'll be doing:\nBuild and own the model serving infrastructure, real-time inference, feature retrieval, and the latency budget that governs both\n\nBuild the deployment path our data scientists use to ship models themselves, including bring-your-own-model support for clients hosting their own\n\nOwn models in production: monitoring, drift detection, retraining, incident response, and the on-call rotation\n\nBuild and optimise the pipelines that turn raw device and behavioural signals into production-ready features\n\nWork across Python and our Go backend to keep inference fast inside the request path\n\nBuild models yourself where it makes sense, roughly 20% of the role, and more if you want it\n\nChampion testing, observability, security and compliance in a regulated environment\n\nWhat you'll need\nExperience building, not just using, model serving infrastructure.\n\nProduction ownership of ML systems: you've been paged when something broke, you found out why, and you changed something so it didn't happen again.\n\nStrong Python, and solid software engineering fundamentals, testing, code review, CI/CD, the discipline that makes a platform other people can rely on.\n\nComfort with Kubernetes, containers and a major cloud (we're mostly GCP), plus infrastructure-as-code.\n\nEnough understanding of models to debug them. You don't need to have trained one recently, but when precision drops you should know the difference between a data problem, a feature pipeline problem, and a model problem\n\nExperience building tooling other engineers or data scientists actually use, and the judgement to know what should be self-serve and what shouldn't.\n\nBonus Points\nDomain knowledge in fraud, risk, or cybersecurity.\n\nFamiliarity with CI/CD, Docker, Kubernetes and the modern devops framework.\n\nUnderstanding of modern browser APIs and high-entropy data collection techniques.\n\nFamiliarity with leveraging frontier LLMs for automation.\n\nBenefits we offer:\nGenerous compensation in cash and equity\n\nEarly exercise for all options, including pre-vested\n\nWork from anywhere: Remote-first Culture\n\nFlexible paid time off and Year-end break\n\nHealth insurance, dental, and vision coverage for employees and dependents - US and Canada specific\n\n4% matching in 401k / RRSP - US and Canada specific\n\nMacBook Pro delivered to your door\n\nOne-time stipend to set up a home office - desk, chair, screen, etc.\n\nMonthly meal stipend\n\nMonthly social meet-up stipend\n\nAnnual health and wellness stipend\n\nAnnual Learning stipend\n\nJoin a fast-growing company with world-class professionals from around the world. If you are seeking a meaningful career, you found the right place, and we would love to hear from you.\nTo learn more about how we process your personal information and your rights in regards to your personal information as an applicant and Sardine employee, please visit our Applicant and Worker Privacy Notice.","description_format":"text","description_chars":5003,"description_truncated":false,"requirements":{"experience_years_min":null,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":null,"security_clearance":false,"languages":[]},"benefits":["401k plan","Apple Macbook","Equity","Health insurance","Home office"],"hiring_locations":[{"name":"United States","iso":"US","kind":"country"},{"name":"Canada","iso":"CA","kind":"country"},{"name":"Mexico","iso":"MX","kind":"region"},{"name":"Anguilla","iso":"AI","kind":"region"},{"name":"Antigua and 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