{"id":1604219,"url":"https://alion.io/job/intuit-staff-machine-learning-engineer-consumer-risk-ai","title":"Staff Machine Learning Engineer, Consumer Risk AI","company":{"id":16628,"name":"Intuit","domain":"intuit.com","url":"https://alion.io/company/intuit","size_band":"1001-5000","is_staffing_agency":false,"employer_type":"direct","is_intermediary":false,"listed_via":null,"ats_vendor":"Radancy","truth_index":{"grade":"B","score":81,"open_postings":70,"ghost_share":0,"stale_share":0.771,"repost_share":0.014,"time_to_fill_p50_days":37,"computed_at":"2026-10-17T05:46:00Z"}},"role":"AI/ML","role_family":"AI/ML","seniority":"staff","employment_type":"full_time","work_mode":"on_site","remote_scope":null,"remote_scope_basis":null,"remote_working_hours":null,"hiring_geo_confidence":"structured","locations":["Mountain View, United States"],"countries":["US"],"hiring_countries":[],"hiring_countries_total":0,"salary":{"min":202500,"max":274000,"currency":"USD","period":"year","gross":null,"usd_annual":274000},"salary_estimate":null,"experience_years_min":8,"visa_sponsorship":false,"relocation_package":false,"has_equity":false,"technologies":[{"name":"AI Agents","optional":false},{"name":"Amazon SageMaker","optional":false},{"name":"Autonomous Navigation","optional":false},{"name":"AWS","optional":false},{"name":"CI/CD","optional":false},{"name":"Feature Store","optional":false},{"name":"Flink","optional":false},{"name":"Machine Learning","optional":false},{"name":"Python","optional":false},{"name":"Spark","optional":false},{"name":"SQL","optional":false}],"status":"live","first_seen_at":"2026-09-29T00:00:00Z","employer_posted_date":"2026-09-29","last_verified_at":"2026-10-19T02:46:23Z","board_verified":true,"closed_at":null,"days_open":20,"trust":{"level":"ok","repost_count":null,"flags":[],"days_open":20},"description":"Intuit is looking for a Staff Machine Learning Engineer to own the data and platform layer beneath our consumer risk decisioning. This team builds the machine learning that decides, in real time, whether money moves - protecting customers from account takeover, first/third-party fraud, and unauthorized transactions across Intuit Fintech products.\nYou'll design and own the shared infrastructure every model on this team depends on: streaming and batch feature pipelines, the cross-entity data path, training and evaluation frameworks, real-time inference serving, and the handoff into our decision engine, across entire Fintech money product lifecycle - from risk screening/qualification of money-in/out events, cashflow underwriting,account take-over detection, to dynamic segmentation. What you architect becomes the reference pattern the whole organization adopts.\nResponsibilities\nOwn the technical vision and architecture for the consumer risk data and serving platform - feature pipelines, the cross-entity data path, training and evaluation infrastructure, and real-time inference - balancing tradeoffs and long-term implications \nDesign and build multi-cloud infrastructure stack and enable data handshake, working through federated account link mapping, and land curated, governed datasets in the Intuit's central data lake\nBuild shared feature infrastructure spanning streaming and batch, consumed by multiple model workstreams, with the observability to catch drift and staleness\nEstablish evaluation frameworks that make model quality, regression, and production impact measurable across the team's portfolio\nOwn the model-to-decision path: deployment through model serving, integration with the decision engine, and correctness and latency on a sub-second decision budget\nSet and enforce engineering standards for ML systems on this team - testing, observability, reproducibility, operational excellence - and structure codebases for agent-assisted development and autonomous navigation\nEngineer closed-loop workflows that automate the repetitive parts of the model lifecycle, moving beyond point automation toward orchestrated systems needing minimal intervention\nEliminate barriers caused by technical and prioritization complexity, including dependencies that cross into platform and data teams - cultivate the partnerships that make those dependencies tractable\nGeneralize what you build into a reference pattern other teams can adopt rather than rebuild, and document it so the pattern travels\nMentor engineers on ML systems craft; provide actionable feedback to senior engineers and help them break work into pieces agents can execute reliably\nConnect technical decisions to the metrics leadership tracks - loss basis points, approval rate, decision latency, hold release rate - define success up front, and drive the post-launch iteration\nQualifications\n Minimum\nBS, MS, or PhD in Computer Science, Engineering, or a related quantitative field, or equivalent practical experience\n8+ years building production software, with substantial time on ML systems rather than ML research; prior experience leading an engineering effort across teams\nStrong CS fundamentals - data structures, algorithms, distributed systems, system design - plus working ML fundamentals (classification, regression, feature engineering, model evaluation)\nProficiency in Python and SQL; production experience with Spark, Flink, or equivalent for streaming and batch data processing\nDemonstrated ownership of a data or ML platform used by more than one team, including the operational load after launch\nExperience deploying models to real-time serving under hard latency budgets, and running them in production afterward\nCloud infrastructure depth in at least one major cloud, ideally AWS (including SageMaker or equivalent ML tooling). Comfortable owning your own footprint - IaC, CI/CD, cost - rather than filing tickets against someone else's\nTrack record of setting technical direction in ambiguous problem spaces and bringing other teams along without formal authority\nStrong written communication. You can put a tradeoff in front of an AI scientist, a platform owner, and a risk strategy partner in one document and have all three follow it\n Preferred\n\nRisk, fraud, payments, or credit domain experience, ideally in real-time decisioning\nFeature store or feature platform experience \nEntity resolution or identity graph work\nExperience with a rules engine and the model-to-decision handoff\nRegulated data handling - field-level encryption, fine-grained access control, data governance in financial services\nFluency orchestrating AI agents on real engineering work, and judgment about where agent-generated output needs deterministic guardrails\nIntuit provides a competitive compensation package with a strong pay for performance rewards approach. This position may be eligible for a cash bonus, equity rewards and benefits, in accordance with our applicable plans and programs (see more about our compensation and benefits at Intuit®: Careers | Benefits). Pay offered is based on factors such as job-related knowledge, skills, experience, and work location. To drive ongoing fair pay for employees, Intuit conducts regular comparisons across categories of ethnicity and gender.\n The expected base pay range for this position is:Mountain View $202,500 - $274,000","description_format":"text","description_chars":5360,"description_truncated":false,"requirements":{"experience_years_min":8,"management_years_min":null,"team_size_min":null,"manages_managers":false,"education":{"level":"bachelor","optional":true},"security_clearance":false,"languages":[]},"benefits":["Equity"],"hiring_locations":[],"hiring_excludes":[],"relocation_offered":false,"industries":["Personal Finance Apps & Education","Accounting & Tax Software","Tax Advisory & Preparation"],"lifecycle":[{"event":"open","at":"2026-10-01T19:43:50Z"}],"visa":[{"country":"US","licensed_sponsor":true,"evidence":"H-1B filings in 12 months: 719 · green card filings: 199","filings_12m":719,"filings_prev_12m":718,"green_card_filings_12m":199,"median_offered_wage_usd":177081,"route":null,"cap_exempt":false,"checked_at":"2026-10-15T11:24:14+00:00","sources":["US Department of Labor: LCA disclosure data (H-1B, H-1B1, E-3)","US Department of Labor: PERM disclosure data (green cards)"],"filings_for_role_12m":306}],"liveness":{"score":55,"band":"ok","label":"Likely open","p_open":1,"p_active":0.61,"p_room":0.9,"age_days":18,"expected_fill_days":37,"reasons":["conf:1","stale_co","velocity","win:mid","comp:brand"],"computed_at":"2026-10-17T05:46:00Z"},"pay":{"stated_usd_annual":274000,"is_top_pay":false},"html_url":"https://alion.io/job/intuit-staff-machine-learning-engineer-consumer-risk-ai","json_url":"https://alion.io/job/intuit-staff-machine-learning-engineer-consumer-risk-ai.json","meta":{"generated_at":"2026-10-19T04:18:23Z","cache_seconds":300,"methodology":"https://alion.io/methodology","terms":"https://alion.io/terms","contact":"https://alion.io/contact","api":"https://alion.io/developers","about":"Alion is a live layer of people, companies and AI agents: who they are, whether they are real and active right now, what they do and how to work with them, readable by people and by agents and paid per call.","catalog":"https://alion.io/catalog.json","usage":{"tier":"crawler_verified","counted_by":"address","units_charged":1,"used_today":2443,"day_limit":null,"remaining_today":null,"minute_limit":300,"resets_at":"2026-10-20T00:00:00Z"}},"offers":[{"id":"company.slices","title":"One company in depth, by slice","status":"live","price":{"credits":0.02,"usd":0.002,"plus_per_slice":{"credits":0.05,"usd":0.005}},"unit":"per company, plus each slice with data","note":"the employer in depth","call":{"mcp_tool":"get_company","arguments":{"id":16628},"rest":"https://alion.io/mcp/rest/get_company?id=16628"},"human":"https://alion.io/catalog?offer=company.slices&for=job%2Fintuit-staff-machine-learning-engineer-consumer-risk-ai"},{"id":"market.stats","title":"A market slice: pay, demand and time to fill","status":"live","price":{"credits":1,"usd":0.1},"unit":"per slice","note":"pay, demand and time to fill for this role and place","call":{"mcp_tool":"market_stats"},"human":"https://alion.io/catalog?offer=market.stats&for=job%2Fintuit-staff-machine-learning-engineer-consumer-risk-ai"},{"id":"job.search","title":"Open jobs by role, technology, place, pay and visa","status":"live","price":{"credits":0.02,"usd":0.002},"unit":"per posting in a list","note":"similar open postings","call":{"mcp_tool":"search_jobs"},"human":"https://alion.io/catalog?offer=job.search&for=job%2Fintuit-staff-machine-learning-engineer-consumer-risk-ai"},{"id":"company.verify","title":"Is this company real and active right now","status":"pilot","price":null,"unit":"per company","request":{"url":"https://alion.io/catalog/request","method":"POST","body":"{\"offer\": \"company.verify\", \"for\": \"job/intuit-staff-machine-learning-engineer-consumer-risk-ai\", \"note\": \"what you need it for\"}"},"human":"https://alion.io/catalog?offer=company.verify&for=job%2Fintuit-staff-machine-learning-engineer-consumer-risk-ai"}]}