Senior Engineering Manager – Machine Learning Data Enablement

🕒 September 22

🇺🇸 United States – Remote

💵 $195k - $270k / year

⏰ Full Time

🟠 Senior

👮‍♀️ Software Engineering Manager

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Upstart

WebsiteLinkedInAll Job Openings

1001 - 5000 employees

🚘 Automotive

💼 Consulting

🏥 Healthcare

Automotive • Consulting • Healthcare

Upstart is a leading AI lending marketplace partnering with banks and credit unions to expand access to affordable credit. The company focuses on revolutionizing lending and credit risk evaluation by leveraging its AI marketplace, which allows for higher approval rates and lower loss rates for Upstart-powered banks and credit unions. Recently, Upstart has expanded its offerings to include automobile refinancing. With a mission to enable effortless credit based on true risk, Upstart is also known for its digital-first lending experience and holds a significant position in the financial services sector.

📋 Description

• Lead Upstart’s ML Data Enablement organization • Define the strategy, operating model, and execution roadmap for ML data enablement • Build and lead a high-performing team spanning data integration, data quality, metadata, and ML-critical infrastructure for online inference and offline training • Establish dedicated integration capacity where needed • Execute technical strategy against metrics such as data evaluation velocity and time to production • Drive data quality and reconciliation frameworks, including retro-versus-production checks, ingress monitoring, and drift detection • Champion company-wide data contracts and SLAs for ML-critical datasets • Establish end-to-end ownership across third-party and internal data lifecycles • Accelerate third-party data onboarding through standardized vendor intake, secure retro ingestion, templated integrations, and configurable microservices • Improve metadata coverage, lineage standards, ownership contracts, and ML discoverability across internal data domains • Partner with ML, ML Platform, Procurement, Data Platform, and product engineering teams

🎯 Requirements

• Bachelor’s degree in Computer Science, Engineering, Mathematics, or a related field, or equivalent experience, plus 8 years of engineering experience • At least 3 years of direct people management experience • Owned production data pipelines enabling both offline training and online inference • Experience building and scaling data systems using modern stacks such as Databricks/Spark, Python, SQL, AWS, streaming systems, and orchestration frameworks • Experience with distributed systems architecture • Ownership of complex cross-functional initiatives spanning engineering, ML, and business stakeholders • Experience delivering under peer pushback and negotiating dependencies • Experience designing and enforcing data quality frameworks and production observability • Experience with reconciliation, drift detection, and incident/postmortem operating loops • Preferred: 10+ years in data engineering and ML platform or ML data platform roles, with 5+ years managing engineering teams • Preferred: feature stores, real-time feature delivery, or equivalent feature transformation interfaces used in inference • Preferred: lakehouse architecture and big data processing frameworks • Preferred: DevOps and infrastructure-as-code practices, including Kubernetes, Terraform, and CI/CD • Preferred: fintech or regulated-environment experience • Preferred: translating technical tradeoffs into business impact and influencing cross-functional strategy

🏖️ Benefits

• Competitive compensation, including base pay, bonus opportunities, and annual equity grants that vest quarterly • Retirement benefits including a 401(k) or Group Retirement Savings Plan with a company match of $2 for every $1 contributed, up to $15,000 annually • Employee Stock Purchase Plan (ESPP) with discounted stock purchase options for eligible employees (US only) • Comprehensive medical, dental, vision, and wellness coverage • Supplemental health coverage for Canada • Health Savings Account contributions for eligible plans (US only) • Life insurance and disability coverage • Paid time off, sick leave, and company holidays • Paid family and parental leave • Family-centered fertility, parenthood, and caregiving benefits • Employee Assistance Program offering mental health support and life-centered resources • Financial planning tools and financial concierge service (US only) • Annual wellness allowance • Annual productivity allowance for relevant tools and resources • Team events, all-company updates, and employee resource groups • Catered lunches and stocked micro-kitchens at offices in the Bay Area, Austin, Columbus, and New York City