Manager, AI/ML Engineering

Stellantis • Auburn Hills, MI

1d

About The Position

The Manager of AI/ML Engineering — North America leads and develops a team of AI/ML engineers while remaining hands-on in designing, building, and shipping complete production AI/ML solutions, including services and user-facing applications. This player-coach role owns team commitments and production health, takes on the most challenging solutions, sets engineering standards, and helps engineers grow. The role is engineering-first and combines data science and machine learning expertise with strong software and solution-delivery capabilities.

Engineering owns products end-to-end, from design through production and ongoing maintenance and optimization. Program and product-management partners provide direction, requirements, and priorities. The manager succeeds by delivering effectively within that partnership, shaping requirements, offering evidence-based pushback, and building trust. The team operates globally, with functional interaction across regions.

The manager leads and coaches engineers, contributes to hiring, and mentors the team toward full-stack AI/ML capabilities. They personally deliver solutions spanning data pipelines, models, inference services, agentic and LLM components, APIs, and user touchpoints such as applications and dashboards. They own production delivery and health, enforce engineering standards, and work with the MLOps team to meet production release and operation readiness standards.

Requirements

• Bachelor’s degree in engineering, computer science, applied mathematics, or a related field, or related field.
• At least 10 years of software engineering experience.
• Substantial hands-on solution-development experience with services, APIs, and user-facing touchpoints or applications, including front-end or full-stack work.
• Experience leading or coordinating a team of engineers.
• Track record of shipping and operating production software, with ownership of systems in production rather than only project delivery.
• Remain hands-on in software development.
• Practical experience delivering AI/ML-powered products.
• Strong Python skills and familiarity with common ML libraries.
• Ability to work across data, modeling, and software concerns.
• Experience with cloud platforms; AWS is preferred.
• Experience with modern data/ML platforms such as Databricks or Spark.

Nice To Haves

• Experience building agentic or LLM-based systems.
• Experience adopting AI-assisted development tools across a team.
• Automotive, industrial, IoT, regulated, or embedded-adjacent domain experience.
• Time-series or vehicle-data experience.
• Familiarity with MLOps concepts, including CI/CD for ML, model registries, monitoring, and retraining.
• Front-end or full-stack delivery experience with dashboards, internal tools, or product UIs.
• A track record as a player-coach, leading a team while continuing to contribute code.

Responsibilities

• Lead and manage an AI/ML engineering team, providing day-to-day direction, coaching, performance management, and career development.
• Manage engineers who may contribute to programs outside the manager’s direct remit, including engineers working from other regions.
• Contribute to hiring by interviewing candidates, raising the engineering craft bar, and helping grow the team.
• Develop engineers toward full-stack AI/ML capabilities across data, modeling, services, and application layers; mentor through code review and pairing.
• Personally design, build, and ship challenging end-to-end solutions, including data pipelines, model and inference services, agentic/LLM components, APIs, applications, and dashboards.
• Spend a substantial share of time building and reviewing code.
• Design and implement ML models for structured, time-series, and unstructured data, and own validation, evaluation, and error analysis for team deliverables.
• Own the team’s delivery of production AI/ML solutions and their production health end-to-end.
• Set and enforce engineering standards for architecture, code review, testing, and CI/CD.
• Work with the dedicated MLOps team, build to its production readiness standards and gates, and route production-driven code changes back through the team.
• Partner with program and product-management teams on scope, priorities, and delivery commitments, and communicate progress with evidence.
• Coordinate with functional leads and globally dispersed project teams, and build products using global platforms and standards.

What This Job Offers

• Job Type: Full-time
• Career Level: Manager