Data and ML Platform Engineering Manager
Job Description:
• Build the team + roadmap
• Stand up a new platform team (hiring, onboarding, team rituals, execution cadence).
• Define a clear, prioritized platform roadmap with measurable adoption outcomes.
• Deliver high-leverage platform components
• Build “paved roads” that make it easy to ship: reusable patterns, templates, libraries, and reference architectures.
• Enable self-service across data + ML workflows with strong governance, security, and observability.
• Use a mix of open source and vendor products to build a Data and ML Platform.
• Run production-grade operations
• Establish quality gates (design reviews, testing strategy, release safety) and platform standards.
• Own operational excellence: SLIs/SLOs, on-call readiness, incident response, capacity planning, cost/performance tradeoffs.
• Partner across the org
• Work closely with Data Engineering, ML Engineering, Analytics, Product, and Security to drive adoption and outcomes.
Requirements:
• A graduate degree in Computer Science, Mathematics, or a related quantitative field.
• 8+ years of engineering experience, with meaningful depth in data and/or ML platforms.
• 3+ years leading engineers (hiring, coaching, delivery accountability).
• Strong distributed systems fundamentals (scaling, reliability, data correctness).
• Hands-on ability in Python and/or Java (can dive into code and unblock delivery).
• Experience with several of: Kubernetes, Spark, Kafka/Flink, orchestration, metadata/governance, table formats (Iceberg), CI/CD, observability, NoSQL stores.
• MLOps experience (ML Flow, feature stores, model lifecycle tooling, deployment patterns).
• Built developer “paved roads” / internal platforms with strong adoption.
• Familiarity with search infrastructure (Turbopuffer/Elasticsearch).
• Self-starter + ownership: drives ambiguous problems to durable solutions.
• Builds and grows teams: mentors, raises the bar, and develops talent.
• Quality-first: designs for operability, correctness, and reliability from day one.
Benefits:
• Company-subsidized medical, dental, & vision plans
• 401(k) plan with company match
• Annual bonus
• Flexible PTO to encourage a healthy work/life balance (2 weeks STRONGLY encouraged!)
• Generous paid leave programs, including 16-week paid parental leave and disability benefits
• Workplace flexibility and modern work schedules focused on getting the job done, not hours clocked
• Company-wide in-person events and team outings
• Lifestyle enhancement program
• Company equipment provided (Windows & Mac options)
• Annual performance reviews with opportunities for growth and career development
Apply Now
Apply Now
• Build the team + roadmap
• Stand up a new platform team (hiring, onboarding, team rituals, execution cadence).
• Define a clear, prioritized platform roadmap with measurable adoption outcomes.
• Deliver high-leverage platform components
• Build “paved roads” that make it easy to ship: reusable patterns, templates, libraries, and reference architectures.
• Enable self-service across data + ML workflows with strong governance, security, and observability.
• Use a mix of open source and vendor products to build a Data and ML Platform.
• Run production-grade operations
• Establish quality gates (design reviews, testing strategy, release safety) and platform standards.
• Own operational excellence: SLIs/SLOs, on-call readiness, incident response, capacity planning, cost/performance tradeoffs.
• Partner across the org
• Work closely with Data Engineering, ML Engineering, Analytics, Product, and Security to drive adoption and outcomes.
Requirements:
• A graduate degree in Computer Science, Mathematics, or a related quantitative field.
• 8+ years of engineering experience, with meaningful depth in data and/or ML platforms.
• 3+ years leading engineers (hiring, coaching, delivery accountability).
• Strong distributed systems fundamentals (scaling, reliability, data correctness).
• Hands-on ability in Python and/or Java (can dive into code and unblock delivery).
• Experience with several of: Kubernetes, Spark, Kafka/Flink, orchestration, metadata/governance, table formats (Iceberg), CI/CD, observability, NoSQL stores.
• MLOps experience (ML Flow, feature stores, model lifecycle tooling, deployment patterns).
• Built developer “paved roads” / internal platforms with strong adoption.
• Familiarity with search infrastructure (Turbopuffer/Elasticsearch).
• Self-starter + ownership: drives ambiguous problems to durable solutions.
• Builds and grows teams: mentors, raises the bar, and develops talent.
• Quality-first: designs for operability, correctness, and reliability from day one.
Benefits:
• Company-subsidized medical, dental, & vision plans
• 401(k) plan with company match
• Annual bonus
• Flexible PTO to encourage a healthy work/life balance (2 weeks STRONGLY encouraged!)
• Generous paid leave programs, including 16-week paid parental leave and disability benefits
• Workplace flexibility and modern work schedules focused on getting the job done, not hours clocked
• Company-wide in-person events and team outings
• Lifestyle enhancement program
• Company equipment provided (Windows & Mac options)
• Annual performance reviews with opportunities for growth and career development
Apply Now
Apply Now