We started Dave for one reason: banks weren’t built for people like us, and we knew we deserved better.
Senior Machine Learning Platform Engineer
Location
United States
Posted
3 days ago
Salary
$150K - $187K / year
Seniority
Senior
Job Description
Senior Machine Learning Platform Engineer
Dave
• Design, build, and evolve core ML platform infrastructure, including feature stores, real-time model scoring services, and systems supporting the full model development, deployment, and monitoring lifecycle. • Drive technical decision-making for complex initiatives, choosing solutions that scale, are testable, and reduce long-term maintenance burden. • Lead and influence system design discussions, clearly articulating trade-offs and aligning solutions with product and business goals. • Set a high bar for code quality and system reliability through exemplary contributions and thoughtful, constructive code reviews. • Identify, communicate, and mitigate technical risks across platform components before they impact members. • Partner closely with data scientists, engineers, and product stakeholders to translate modeling and business needs into durable platform capabilities. • Provide clear, reliable estimates for complex projects, including assumptions, risks, and dependencies. • Improve team processes, tooling, and standards to increase engineering quality and delivery velocity. • Mentor and support other engineers through design feedback, code reviews, and onboarding. • Participate in hiring and interviews, helping raise the technical bar through well-calibrated feedback.
Job Requirements
- Bachelor’s degree in Computer Science or a related field, or equivalent practical experience. Advanced degrees are a plus.
- 5+ years of professional software engineering experience, with a focus on backend, platform, or infrastructure engineering.
- Deep expertise in Python; proficiency in an additional language is a plus.
- Strong experience building or operating scalable, high-availability distributed systems in a cloud environment (GCP, AWS).
- Experience working with ML systems from an infrastructure perspective, including deployment, serving, monitoring, and data access.
- Proficiency with SQL and relational databases; familiarity with Snowflake or non-relational systems is a plus.
- Experience leading complex technical projects from design through production.
- Experience with MLOps tooling or feature store architectures is a nice to have.
- Experience with workflow orchestration tools (e.g., Airflow) and large-scale data processing frameworks (e.g., Spark, Beam) is also a nice to have.
- Background building data-intensive or real-time systems is a nice to have.
Benefits
- Premium Medical, Dental, and Vision Insurance plans
- Generous paid parental and caregiver leave
- 401(k) savings plan with matching contributions
- Flexible PTO and generous company holidays, including Juneteenth and Winter Break
- Flexible hours and virtual-first work culture with a home office stipend
- Financial advisor and financial wellness support
- Opportunity to tackle tough challenges, learn and grow from fellow top talent, and help millions of people reach their personal financial goals
- All-company in-person events once or twice a year and virtual events throughout to connect with your team members and leadership team
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