[Hiring] Senior Engineering Manager - Machine Learning Data Enablement @Upstart

Role Description

As the Sr. Engineering Manager - ML Data Enablement, you will lead this organization and define the strategy, operating model, and execution roadmap that increases data evaluation velocity and reduces time-to-production for high-value data sources. You will partner cross-functionally with ML, ML Platform, Procurement, Data Platform, and product engineering teams to transform data from a bottleneck into a durable competitive advantage.

• Build and lead a high-performing team spanning data integration, data quality, metadata, and ML-critical data infrastructure for online inference and offline training, including standing up new dedicated integration capacity where needed.
• Set and execute the technical strategy aligned to measurable north star metrics such as increasing data evaluation velocity and reducing time to production.
• Drive robust data quality and reconciliation frameworks, including retro vs. production checks, ingress-level monitoring, and drift detection to prevent launch issues and downstream model degradation.
• Champion a company-wide shift toward data contracts and SLAs, ensuring data producers adopt clear ownership, quality standards, and monitoring practices for ML-critical datasets.
• Establish clear end-to-end ownership across the third-party and internal data lifecycle, eliminating fragmented workflows and implicit accountability.
• Accelerate third-party data onboarding by operationalizing standardized vendor intake, secure retro ingestion, templated integrations, and configurable microservices that reduce engineering lift and cycle time.
• Unlock internal data for ML innovation by improving metadata coverage, lineage standards, ownership contracts, and ML discoverability across high-impact internal domains.

Qualifications

• Bachelor’s degree in Computer Science, Engineering, or Mathematics, or a related field (or its equivalent) + 8 years of engineer experience, including at least 3 years of direct people management experience.
• Owned production data pipelines that enable both offline training and online inference.
• Proven experience building and scaling data systems in modern stacks (e.g., Databricks/Spark, Python, SQL, AWS, streaming systems, orchestration frameworks) and distributed systems architecture.
• Demonstrated ownership of complex cross-functional initiatives spanning engineering, ML, and business stakeholders, including delivery under peer pushback and dependency negotiation.
• Experience designing and enforcing data quality frameworks and observability for production systems, including reconciliation, drift detection, and incident/postmortem operating loops.

Requirements

• 10+ years in data engineering AND ML platform OR ML data platform roles, with 5+ years managing engineering teams (strongly preferred).
• Experience with feature stores and real-time feature delivery or equivalent feature transformation interfaces used in inference.
• Strong knowledge of lakehouse architecture and big data processing frameworks.
• Familiarity with DevOps and infrastructure-as-code practices (Kubernetes, Terraform, CI/CD).
• Experience in fintech or other regulated environments where explainability, auditability, and controls matter.
• Ability to translate complex technical tradeoffs into business impact and influence cross-functional strategy.

Benefits

• Competitive compensation, including base pay, bonus opportunities, and annual equity grants that vest quarterly.
• Retirement benefits to help you plan for the future, including a 401(k) or Group Retirement Savings Plan with a company match of $2 for every $1 contributed, up to $15,000 annually (USD in the US, CAD in Canada).
• Employee Stock Purchase Plan (ESPP) with discounted stock purchase options for eligible employees (US only).
• Comprehensive health coverage designed to support you and your family, including medical, dental, vision, and wellness resources for US and supplemental health coverage for Canada.
• Health Savings Account contributions from Upstart for eligible plans (US only).
• Income protection benefits, including life insurance and disability coverage for added financial security.
• Paid time off, sick leave, and company holidays, in line with local requirements.
• Paid family and parental leave to support caregiving and major life moments (duration varies by country).
• Family-centered benefits to support fertility, parenthood, and caregiving needs.
• Employee Assistance Program (EAP) offering mental health support and life-centered resources.
• Financial wellness resources, including access to financial planning tools and a financial concierge service (US Only).
• Annual wellness allowance to support your physical and emotional well-being and personal development, based on what matters most to you.
• Annual productivity allowance to invest in relevant tools and resources you need to do your best work, no matter where you work from.
• Connection and community through team events, all-company updates, and employee resource groups (ERGs).
• Onsite perks, including catered lunches and fully stocked micro-kitchens when working from one of our offices in the Bay Area, Austin, Columbus, and New York City.