Hands-on AI/ML Engineering Lead (Global)

Stellantis NV; Auburn (AL); On-site; USD 180,000 - 240,000; Full time

Benefits offered by this job

Health & wellbeing coverage

17+ paid holidays

401k matching

Disability & life insurance

Company vehicle lease program

Family building benefits

Tuition reimbursement & student loan I

Volunteer hours

Job summary

Stellantis NV in North America seeks a Manager of AI/ML Engineering to lead a mixed team of data scientists and engineers. The role blends coaching with hands-on design, building, and shipping production AI/ML solutions including user-facing apps and dashboards.

You will own the team’s delivery, set engineering standards, and collaborate with MLOps and product partners to drive production readiness and platform-scale impact across regions.

Qualifications

• Bachelor's degree in engineering, computer science, applied mathematics, or a related field.
• At least 10 years in software engineering with hands-on solution development and team leadership.
• Track record of shipping and operating production software with current hands-on involvement.
• Experience delivering ML/AI-powered products.
• Strong Python and ML libraries; cross-domain data, modeling, software.
• Cloud (AWS preferred) and modern data/ML platforms (Databricks/Spark).

Responsibilities

• Lead and coach an AI/ML engineering team — day-to-day direction, performance, and career development.
• Personally own and ship hard solutions end-to-end — data pipelines, models, APIs, and user touchpoints.
• Own team delivery of production AI/ML solutions and their health end-to-end.
• Partner with program and product-management teams on scope, priorities, and delivery commitments.

Skills

Leadership

Python

ML/AI

Full-stack software

Education

Bachelor's degree in engineering, computer science, applied mathematics, or related field

Tools

AWS

Databricks/Spark

CI/CD

Job description

Stellantis NV in North America seeks a Manager of AI/ML Engineering to lead a mixed team of data scientists and engineers. The role blends coaching with hands-on design, building, and shipping production AI/ML solutions including user-facing apps and dashboards.

You will own the team’s delivery, set engineering standards, and collaborate with MLOps and product partners to drive production readiness and platform-scale impact across regions.