{"id":1476264,"url":"https://alion.io/job/tabs-research-engineer-aiml","title":"Research Engineer, AI/ML","company":{"id":717047,"name":"Tabs","domain":"tabs.com","url":"https://alion.io/company/tabs-4","size_band":"51-200","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Ashby","truth_index":{"grade":"A","score":87,"open_postings":3,"ghost_share":0,"stale_share":0.333,"repost_share":0,"time_to_fill_p50_days":68,"computed_at":"2026-10-01T05:45:00Z"}},"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":["New York, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":170000,"max":235000,"currency":"USD","period":"year","gross":null,"usd_annual":235000},"salary_estimate":null,"experience_years_min":3,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Embeddings","optional":false},{"name":"LLM","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Reranking","optional":false},{"name":"TypeScript","optional":false}],"status":"live","first_seen_at":"2026-09-29T14:15:35Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-10-01T18:30:41Z","board_verified":true,"closed_at":null,"days_open":2,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":2},"description":"Tabs is the AI Operating System for Revenue, built for modern finance and accounting teams. It combines deep revenue and accounting expertise with the agents and applications needed to run revenue work end to end. Tabs understands customer and contract context, applies accounting logic, and executes critical workflows with built in controls, auditability, and human oversight. With Tabs, finance teams can move from manually managing revenue workflows to directing outcomes while the system executes the work.\nThe Job\nYou’ll work on a fast-moving AI team, owning problems from initial exploration through production.\nTurn messy financial data and ambiguous problems into working AI products, starting with simple baselines and adding complexity only when it earns its keep\n\nBuild evaluations that reflect real user outcomes, then use error analysis, ablations, and production feedback to make the system better\n\nMake practical tradeoffs across model quality, cost, latency, determinism, reliability, and maintainability\n\nPartner closely with product and engineering to build AI features that take real work off finance teams’ plates\n\nWhat You Bring\nStrong statistical and machine learning fundamentals, with good judgment about when the answer is classical ML, an LLM, agents, or something in between\n\nExperience shipping ML or AI systems end-to-end, from data and evaluation through production\n\nComfort making progress with noisy data, weak labels, incomplete specifications, and imperfect supervision\n\nExperience across several of: classical ML, embeddings, retrieval and reranking, similarity search, model evaluation, LLM applications, and agentic systems\n\nStrong Python skills and the ability to contribute to production software; TypeScript or modern web application experience is a plus\n\nExperience and education\nWe welcome a range of backgrounds. Successful candidates will typically have one of the following:\nA bachelor’s degree in a relevant quantitative field plus 3+ years of relevant industry or applied research experience\n\nA relevant master’s degree plus 1+ year of relevant industry or applied research experience\n\nA relevant PhD; doctoral research counts as relevant experience, with 3 years of substantive doctoral research considered equivalent to the experience above\n\nEquivalent practical experience demonstrated through shipped systems, independent research, open-source work, or another nontraditional path\n\nHow We Work\nWe’re a small team, so everyone has a hand in deciding what to build and making it work in the real world.\nWe ship, learn from real usage, and iterate\n\nWe make assumptions explicit, follow the evidence, and communicate tradeoffs clearly\n\nWe stick with hard problems and welcome better ideas, regardless of where they come from\n\nWe help where the team needs us, even when it falls outside our immediate scope\n\nWe collaborate closely in person five days a week\n\nNo one gets extra points for making the solution more complicated than the problem.\nEven if you don’t meet every qualification, we encourage you to apply. We care most about curiosity, craft, judgment, and drive.\nPerks and Benefits (Full-time Employees)\nCompetitive compensation and equity\n\nUnlimited PTO\n\nUp to 100% employer covered monthly healthcare premium (medical, dental, vision)\n\nLunch provided via Sharebite, plus dinner for any later in office days.\n\nParental leave up to 12 weeks\n\nTax free commuter and parking benefits\n\nVoluntary insurances (Life, Hospital, Critical Illness, Accident)\n\nEmployee Assistance Program (Rightway)\n\nFree One Medical Membership\n\n401k\n\nTabs is an equal opportunity employer. We welcome teammates of all identities and do not discriminate on the basis of race, ethnicity, religion, gender identity, sexual orientation, age, disability, veteran status, or any other protected characteristic. We’re committed to creating an environment where everyone can grow, contribute, and feel comfortable being themselves.","description_format":"text","description_chars":3952,"description_truncated":false,"requirements":{"experience_years_min":3,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":false},"security_clearance":false,"languages":[]},"benefits":["401k plan","Equity","Parental leave","Unlimited PTO"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Billing & Subscription Management","Financial AI","Document AI","Accounting & Tax Software"],"lifecycle":[{"event":"open","at":"2026-09-29T18:54:08Z"}],"liveness":{"score":90,"band":"hot","label":"Hiring now","p_open":1,"p_active":0.903,"p_room":1,"age_days":1,"expected_fill_days":68,"reasons":["conf:7","velocity","win:early"],"computed_at":"2026-10-01T05:45:00Z"},"pay":{"stated_usd_annual":235000,"is_top_pay":true},"html_url":"https://alion.io/job/tabs-research-engineer-aiml","json_url":"https://alion.io/job/tabs-research-engineer-aiml.json","meta":{"generated_at":"2026-10-01T18:56:32Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","usage":{"tier":"crawler","counted_by":"address","units_charged":1,"used_today":1190,"day_limit":5000,"remaining_today":3810,"minute_limit":60,"resets_at":"2026-10-02T00:00:00Z"}}}