Manager, AI/ML Engineering

Role Summary:

How We Operate:

Key Responsibilities:

• Team leadership & growth Lead and manage a AI/ML engineering team of engineers — day-to-day direction, coaching, performance, and career development. Some of these engineers may functionally work on programs outside your direct remit, and you will manage engineers that contribute to your programs from other regions. Contribute to hiring: interview, raise the bar on engineering craft, and help grow the team through the active pipeline. Develop engineers toward the full-stack AI/ML profile (data, modeling, services, application layers); mentor through code review and pairing.
• Lead and manage a AI/ML engineering team of engineers — day-to-day direction, coaching, performance, and career development. Some of these engineers may functionally work on programs outside your direct remit, and you will manage engineers that contribute to your programs from other regions.
• Contribute to hiring: interview, raise the bar on engineering craft, and help grow the team through the active pipeline.
• Develop engineers toward the full-stack AI/ML profile (data, modeling, services, application layers); mentor through code review and pairing.
• Hands-on delivery (player-coach) Personally own and ship hard solutions end-to-end — data pipelines, model/inference services, agentic/LLM components, APIs, and the user touchpoints (apps, dashboards) on top. Spend a substantial share of your time building and reviewing code — you stay in the work, not just over it. Design and implement ML models on structured, time-series, and unstructured data; own validation, evaluation, and error analysis on the team’s deliverables.
• Personally own and ship hard solutions end-to-end — data pipelines, model/inference services, agentic/LLM components, APIs, and the user touchpoints (apps, dashboards) on top.
• Spend a substantial share of your time building and reviewing code — you stay in the work, not just over it.
• Design and implement ML models on structured, time-series, and unstructured data; own validation, evaluation, and error analysis on the team’s deliverables.
• Solution & product delivery – Own the team’s delivery of production AI/ML solutions and their production health end-to-end. Set and enforce engineering standards — architecture, code review, testing, CI/CD. Work closely with the dedicated MLOps team and hand off for production release and operation Build to their readiness standards and gates, and route production-driven code changes back through your team.
• Own the team’s delivery of production AI/ML solutions and their production health end-to-end.
• Set and enforce engineering standards — architecture, code review, testing, CI/CD.
• Work closely with the dedicated MLOps team and hand off for production release and operation
• Build to their readiness standards and gates, and route production-driven code changes back through your team.
• Cross-functional leadership Partner with program and product-management teams on scope, priorities, and delivery commitments; communicate progress with evidence. Operate within a global organization Coordinate with functional leads and globally dispersed project teams Build products with global platforms and standards.
• Partner with program and product-management teams on scope, priorities, and delivery commitments; communicate progress with evidence.
• Operate within a global organization
• Coordinate with functional leads and globally dispersed project teams
• Build products with global platforms and standards.

Basic Qualifications:

• Bachelor’s degree in engineering, computer science, applied mathematics, or a related field, or related field.
• A minimum of 8 years in software engineering, including substantial hands-on solution development — services, APIs, and user-facing touchpoints/apps (front-end/full-stack) — and experience leading or coordinating a team of engineers.
• A track record of shipping and operating production software — you have owned systems in production, not just delivered projects — and you remain hands-on today.
• Practical experience delivering ML/AI-powered products.
• Strong Python and common ML libraries; ability to work across data, modeling, and software concerns.
• Cloud (AWS preferred) and modern data/ML platforms (e.g. Databricks/Spark).

Preferred Qualifications:

• Experience building agentic/LLM-based systems and adopting AI-assisted development tooling across a team.
• Automotive, industrial, IoT , or other regulated/embedded-adjacent domain experience; time-series or vehicle data a plus.
• Familiarity with MLOps concepts (CI/CD for ML, model registry, monitoring, retraining).
• Front-end/full-stack delivery experience (dashboards, internal tools, product UIs).
• A track record as a player-coach — leading a team while still contributing code.

Health & Wellbeing

Compensation, Savings, and Retirement

• Annual Incentive Plan (SAIP), 401k with Employer Match & Contribution (max 8%), SoFi Student Loan Refinancing.

Time Away from Work

Family Benefits

• 12 Weeks paid Parental Leave, Domestic Partner Benefits, Family Building Benefit, Marketplace, Life/Disability and other Insurances.

Professional Growth

Company Car & More

EOE/Disability/Veteran