Staff ML Engineer, Product

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., * 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 its 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.

• 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.

• Competitve Pay
• 401k Matching
• Unlimited PTO
• Lunch daily (in-office only)
• Snacks & Coffee (in-office only)
• Commuter benefits (in-office only), Salary range of $210,000 - $260,000/year + bonus + benefits. Base pay offered may vary depending on job-related knowledge, skills, and experience.