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HomeCompaniesRocket MoneyStaff ML Engineer, Product

Staff ML Engineer, Product

Rocket Money · San Francisco, CA, Washington, D.C., New York City, N.Y., Denver, CO · Remote · Active · $210,000–$260,000 / year · Greenhouse

Job facts

FieldValue
CompanyRocket Money
TitleStaff ML Engineer, Product
Normalized title-
Department / teamData
LocationSan Francisco, CA, United States
Work modelRemote / Remote
Employment type-
Salary$210,000–$260,000 / year
Statusactive
ATS providerGreenhouse
Posted / first seen2025-07-23 / 2026-05-29
Changed / last seen2026-05-29 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from Rocket Money.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Greenhouse.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in San Francisco.Open
Department jobsActive postings in Data.Open
Work model jobsActive Remote postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyRocket Money
Sourcee4537714-8be5-4ba1-afef-8ccb927867a1
ATS providerGreenhouse

Description

The ideal candidate is local to and interested in working from any of our offices (Silver Spring, NYC, SF, Miami, Denver) local to them 1-2x per week. ABOUT ROCKET MONEY 🔮 Rocket Money's mission is to empower people to live their best financial lives. Rocket Money offers members a unique understanding of their finances and a suite of valuable services that save them time and money – ultimately giving them a leg up on their financial journey. ABOUT THE TEAM 🤝 Machine Learning Engineers at Rocket Money further our mission by building products that deepen customer relationships with our many financial products. Our work ranges from transaction enrichment to personalization to cross-functional tools that support various AI product initiatives. We work closely with product teams to develop features that help customers understand, track, and improve their personal finances. We have a strong preference for team players that are comfortable collaborating across teams, know how to support strategy with ML and AI powered user experiences, can deliver scalable and high quality user experiences, and understand the effects of their products on end users. At the Staff level, Machine Learning Engineers are expected to build broad expertise into our products and the ML solutions that power them as well as drive technical progress for the team. ABOUT THE ROLE 🤹 As a Staff Machine Learning Engineer at Rocket Money, you will be at the forefront of our ML and AI product development, bringing your expertise to design, implement, and maintain sophisticated ML systems that drive our product experiences. You will: Lead the architecture and development of complex AI and ML powered features across Rocket Money's product suite, proactively identifying technical challenges before they become issues. Design, implement, and maintain robust evaluation frameworks. You ensure that ML/AI systems can be constantly improved and create frameworks so that others can do the same. Develop novel new product experiences that you are uniquely positioned to enable for users. Help Rocket Money capitalize on it’s unique dataset and scale. Guide others to help generate impact through effective technical leadership and partnership with product. Own end to end development and implementation of ML and AI product features in collaboration with cross-functional product development teams. Rigorous technical critique and oversight coupled with effective communication of business impact are musts. Provide technical mentorship, fostering an environment where everyone can contribute to high-impact work. You will raise the level of everyone around you. Potential Projects: Develop comprehensive evaluation and ML Ops frameworks that enable systematic assessment of model performance, supporting rapid iteration and improvement of AI/ML product features. Scale transaction metadata generation systems to billions of financial transactions in a consumer facing app. Implement AI assisted transaction management and personalization features such as personalized categories, income and rent detection, and subscription identification. Implement effective user feedback mechanisms that enable measurement of ML feature product quality and constant improvement. Architect user facing predictive features that depend on fast moving and large scale user transaction data. ABOUT YOU 🦄 8+ years of professional experience in machine learning engineering or data science roles, with a proven track record of designing and implementing ML systems at consumer tech scale and speed. Extensive hands-on experience integrating ML and AI methods into production workflows, including creating evaluation tooling and effective user feedback mechanisms to support rapid product development cycles and systematic model evaluation. Experience with prompt engineering and management, creating robust systems for testing and optimizing LLM-based applications. Expert-level proficiency in Python, SQL, and at least a handful of common ML frameworks. Working Typescript knowledge is a plus. You understand ML methods at a fundamental level - deep experience in NLP techniques is a plus. You are a master at taking ambiguous problems, creating clarity, and breaking down work into manageable chunks for implementation. You’ve owned the development, launch, and maintenance for several scaled ML/AI powered product experiences. You understand basic software engineering and computer science fundamentals and have applied them at consumer grade scale to build ML powered products in production environments. You are a technical leader who can identify both emergent technical opportunities and gaps relative to best practice. Your strong communication skills enable your team to capitalize on these opportunities and generate impact. You care about products and user experiences, not publications . You are a practitioner first and thrive at the (messy) intersection of the real world and cutting edge approaches. WE OFFER 💫 Health, Dental & Vision Plans Competitive Pay 401k Matching Unlimited PTO Lunch daily (in-office only) Snacks & Coffee (in-office only) Commuter benefits (in-office only) Additional information: Salary range of $210,000 - $260,000/year + bonus + benefits. Base pay offered may vary depending on job-related knowledge, skills, and experience. Rocket Money is an Affirmative Action and Equal Opportunity Employer. All qualified applicants will receive consideration for employment without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, or protected veteran status and will not be discriminated against on the basis of disability. Pursuant to the San Francisco Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.

Full job record

Job IDe34953b7af7bba96e99a55c7d619eac346caebbd
Org ID96679e5b-e87c-4b1b-af39-331023fa6fd9
Source IDe4537714-8be5-4ba1-afef-8ccb927867a1
Board IDe4537714-8be5-4ba1-afef-8ccb927867a1
Providergreenhouse
Provider Job Key6657749003
TitleStaff ML Engineer, Product
Normalized Title
Statusactive
Activeyes
Location TextSan Francisco, CA, Washington, D.C., New York City, N.Y., Denver, CO
DepartmentData
Team
Employment Type
Workplace Typeremote
Remote Policyremote
CountryUnited States
RegionCA
CitySan Francisco
Salary RawSalary range of $210,000 - $260,000/year + bonus + benefits
Salary Min210,000
Salary Max260,000
Salary CurrencyUSD
Salary Periodyear
Source URLhttps://job-boards.greenhouse.io/truebill/jobs/6657749003
Apply URLhttps://job-boards.greenhouse.io/truebill/jobs/6657749003
First Seen At2026-05-29 22:43:15Z
Last Seen At2026-06-06 07:35:28Z
Last Checked At2026-06-06 07:35:28Z
Last Changed At2026-05-29 22:43:15Z
Inactive At
Source Posted At2025-07-23 01:57:33Z
Source Updated At2026-01-09 20:20:39Z
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=greenhouse/board=truebill/date=2026-06-06/2026-06-06T07-35-28-667Z-2c3462cc2e8f296f87977f7e873af133bbec64d9870a8a113fcca238173e5004.json
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Parsed Structured
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Extensions
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