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Mlops Machine Learning Engineer Jobs in Detroit, MI

Staff Machine Learning Engineer - Mapping

Warren, MI · On-site

$185K - $335K/yr

  • Medical

  • Dental

  • Vision

  • Life

  • Retirement

  • PTO

The Role We are looking for a Staff Machine Learning Engineer to serve as a technical leader for automated map reconstruction within our Mapping Engineering team. In this role, you will architect and ...

In order to set you up for success as a Machine Learning Engineer at Wayve, we're looking for the following skills and experience. Essential * Extensive and proven track record of shipping deep ...

Showing results 41-60

Mlops Machine Learning Engineer information

See Detroit, MI salary details

$31.2K

$127.5K

$191.6K

How much do mlops machine learning engineer jobs pay per year?

As of Aug 18, 2026, the average yearly pay for mlops machine learning engineer in Detroit, MI is $127,477.00, according to ZipRecruiter salary data. Most workers in this role earn between $100,500.00 and $153,400.00 per year, depending on experience, location, and employer.

What does an MLOps machine learning engineer do?

An MLOps Machine Learning Engineer bridges the gap between data science and IT operations by developing, deploying, and maintaining machine learning models in production environments. They are responsible for automating workflows, managing model versioning, monitoring performance, and ensuring scalability and reliability of ML systems. Their work enables organizations to deploy machine learning solutions efficiently and consistently, making it easier to update and manage models as business needs evolve.

What are the key skills and qualifications needed to thrive as an MLOps machine learning engineer?

To thrive as an MLOps Machine Learning Engineer, you need a strong background in machine learning concepts, software engineering, and cloud infrastructure, typically supported by a degree in computer science or a related field. Familiarity with tools like Docker, Kubernetes, CI/CD pipelines, cloud platforms (AWS, GCP, Azure), and certifications such as Google Professional Machine Learning Engineer are highly beneficial. Strong problem-solving abilities, collaboration, and communication skills help you work effectively across data science and engineering teams. These skills are essential for reliably deploying, monitoring, and maintaining scalable machine learning solutions in production environments.

How does an MLOps machine learning engineer typically collaborate with data scientists and software engineers during the deployment of machine learning models?

An MLOps Machine Learning Engineer acts as a bridge between data scientists and software engineers, ensuring machine learning models transition smoothly from development to production. They often work closely with data scientists to understand model requirements, data pipelines, and performance metrics, while also collaborating with software engineers to integrate models into scalable systems. Regular communication, shared documentation, and joint troubleshooting sessions are common, as the role requires aligning model performance with system reliability and maintainability. This collaborative environment helps ensure that models are robust, scalable, and impactful in real-world applications.

What is the difference between Mlops Machine Learning Engineer vs Data Scientist?

AspectMlops Machine Learning EngineerData Scientist
Required CredentialsBachelor's or master's in CS, data science, or related fields; certifications in cloud platforms or MLOps toolsBachelor's or master's in statistics, data science, or related fields; certifications in data analysis or machine learning
Work EnvironmentFocus on deploying, maintaining, and scaling ML models in production environmentsFocus on data analysis, model development, and insights generation
Employer & Industry UsageTech companies, startups, enterprises implementing ML solutionsResearch institutions, analytics firms, tech companies for data insights

While both roles involve machine learning, Mlops Machine Learning Engineers specialize in deploying and maintaining models in production, ensuring scalability and reliability. Data Scientists primarily focus on developing models and analyzing data to generate insights. The roles often overlap but differ in their core responsibilities and work environments.

Are MLOps machine learning engineers in demand?

MLOps machine learning engineers are in high demand due to the increasing adoption of AI and machine learning across industries. They are needed to develop, deploy, and maintain scalable ML systems, often requiring skills in cloud platforms, automation, and tools like Docker and Kubernetes. The role offers strong job growth prospects and competitive salaries.

Do MLOps Machine Learning Engineers need a degree?

MLOps Machine Learning Engineers typically do not require a formal degree but often have a background in computer science, data science, or related fields. Practical skills in machine learning, cloud platforms, and tools like Docker, Kubernetes, and CI/CD pipelines are highly valued. Certifications and hands-on experience can also enhance job prospects.

What are popular job titles related to Mlops Machine Learning Engineer jobs in Detroit, MI?

For Mlops Machine Learning Engineer jobs in Detroit, MI, the most frequently searched job titles are:

What cities near Detroit, MI are hiring for Mlops Machine Learning Engineer jobs?

Cities near Detroit, MI with the most Mlops Machine Learning Engineer job openings:

Infographic showing various Mlops Machine Learning Engineer job openings in Detroit, MI as of August 2026, with employment types broken down into 1% As Needed, 76% Full Time, 21% Part Time, and 2% Contract. Highlights an 88% Physical, 2% Hybrid, and 10% Remote job distribution, with an average salary of $127,477 per year, or $61.3 per hour.

Staff Machine Learning Engineer - Mapping

General Motors

Warren, MI • On-site

$185K - $335K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 12 days ago


General Motors rating

8.2

Company rating: 8.2 out of 10

General Motors

Based on 306 frontline employees who took The Breakroom Quiz

7.4

Company rating compared to similar companies: 7.4 out of 10

Automakers average

Based on 6,287 frontline employees who took The Breakroom Quiz


Job description

Job Description

Our Mapping organization is building national-scale, next-generation mapping systems that move beyond static HD maps toward automated, ML-driven map reconstruction pipelines powered by onboard sensor data. These systems form a critical foundation for localization, perception, simulation, and autonomy at scale.

The Role

We are looking for a Staff Machine Learning Engineer to serve as a technical leader for automated map reconstruction within our Mapping Engineering team.

In this role, you will architect and deliver end-to-end ML and computer vision pipelines that reconstruct, validate, and maintain map primitives (e.g., lanes, boundaries, traffic controls, signs) from large-scale sensor data. Your work will directly power next-generation maps that operate reliably across national deployments and evolving road conditions.

This is a hands-on technical leadership role. You will operate with high autonomy, define technical strategy in ambiguous problem spaces, and lead cross-functional efforts spanning Mapping, Perception, Localization, Simulation, and Infrastructure. You will also mentor senior engineers and help raise the ML and CV bar across the organization.

What You'll Do (Responsibilities)
  • Architect and lead ML-driven map reconstruction systems that operate at national scale using multi-modal sensor data (camera, lidar, radar, vehicle signals).

  • Design and implement end-to-end pipelines for offline map reconstruction, including data mining, labeling strategies, model training, evaluation, and production deployment.

  • Define technical strategy and system architecture for next-generation mapping capabilities, balancing ML innovation with robustness, safety, and operational scalability.

  • Lead the development and adoption of state-of-the-art computer vision and ML techniques (e.g., detection, segmentation, 3D reconstruction, BEV representations) applied to mapping problems.

  • Own cross-functional technical initiatives, working closely with Perception, Localization, Simulation, and Platform teams to define interfaces, data contracts, and integration points.

  • Drive technical excellence through design reviews, mentorship, and technical guidance for senior and staff-level engineers across teams.

  • Diagnose and resolve system-level issues across data pipelines, ML models, and production workflows.

  • Serve as a Subject Matter Expert (SME) for ML-based mapping and reconstruction within Mapping and across the AV organization.

  • Contribute to technical roadmaps, hiring, and capability building for ML and CV expertise within the Mapping org.

Minimum Qualifications (Must-Have)
  • 5+ years of experience building and deploying machine learning or computer vision systems in production environments.

  • Strong foundation in computer vision, machine learning, or robotics, with hands-on experience designing and training ML models.

  • Proficiency in Python for ML development; familiarity with C++ or other systems languages is a plus.

  • Experience building large-scale data pipelines for ML, including dataset curation, labeling workflows, training, and evaluation.

  • Proven ability to lead complex, cross-functional technical initiatives with high autonomy and influence.

  • BS, MS, or PhD in Computer Science, Electrical Engineering, Robotics, or a related technical field, or equivalent industry experience.

  • Strong systems thinking - ability to reason about end-to-end ML systems, not just individual models.

Preferred Qualifications (Nice-to-Have)
  • Experience with mapping, localization, perception, or robotics systems, particularly in autonomous driving or mobile robotics.

  • Hands-on experience with 3D perception, BEV representations, or multi-view geometry.

  • Familiarity with AV sensor data (camera, lidar, radar) and real-world data challenges (noise, drift, long-tail scenarios).

  • Experience deploying ML models into production pipelines with monitoring, validation, and iteration loops.

  • Exposure to simulation-based validation, synthetic data, or map change detection workflows.

  • Experience mentoring senior engineers or acting as a technical lead across multiple teams.

Compensation: The compensation information is a good faith estimate only. It is based on what a successful applicant might be paid in accordance with applicable state laws. The compensation may not be representative for positions located outside of New York, Colorado, California, or Washington.

  • The salary range for this role: is$185,100 to $335,300. The actual base salary a successful candidate will be offered within this range will vary based on factors relevant to the position.

  • Bonus Potential: An incentive pay program offers payouts based on company performance, job level, and individual performance.

  • Benefits: GM offers a variety of health and wellbeing benefit programs. Benefit options include medical, dental, vision, Health Savings Account, Flexible Spending Accounts, retirement savings plan, sickness and accident benefits, life insurance, paid vacation & holidays, tuition assistance programs, employee assistance program, GM vehicle discounts and more.

Company Vehicle: Upon successful completion of a motor vehicle report review, you will be eligible to participate in a company vehicle evaluation program, through which you will be assigned a General Motors vehicle to drive and evaluate. Note: program participants are required to purchase/lease a qualifying GM vehicle every four years unless one of a limited number of exceptions applies.

#GM-AV-1

This role is based remotely, but if the selected candidate lives within a specific mile radius of a GM hub, they will be expected to report to the location three times a week {or other frequency dictated by your manager}. This job may be eligible for relocation benefits.

About GM

Our vision is a world with Zero Crashes, Zero Emissions and Zero Congestion and we embrace the responsibility to lead the change that will make our world better, safer and more equitable for all.

Why Join Us

We believe we all must make a choice every day - individually and collectively - to drive meaningful change through our words, our deeds and our culture. Every day, we want every employee to feel they belong to one General Motors team.

Benefits Overview

From day one, we're looking out for your well-being-at work and at home-so you can focus on realizing your ambitions. Learn how GM supports a rewarding career that rewards you personally by visiting Total Rewards resources.

Non-Discrimination and Equal Employment Opportunities (U.S.)

General Motors is committed to being a workplace that is not only free of unlawful discrimination, but one that genuinely fosters inclusion and belonging. We strongly believe that providing an inclusive workplace creates an environment in which our employees can thrive and develop better products for our customers.

All employment decisions are made on a non-discriminatory basis without regard to sex, race, color, national origin, citizenship status, religion, age, disability, pregnancy or maternity status, sexual orientation, gender identity, status as a veteran or protected veteran, or any other similarly protected status in accordance with federal, state and local laws.

We encourage interested candidates to review the key responsibilities and qualifications for each role and apply for any positions that match their skills and capabilities. Applicants in the recruitment process may be required, where applicable, to successfully complete a role-related assessment(s) and/or a pre-employment screening prior to beginning employment. To learn more, visit How we Hire.

Accommodations

General Motors offers opportunities to all job seekers including individuals with disabilities. If you need a reasonable accommodation to assist with your job search or application for employment, email us or call us at 1-800-865-7580. In your email, please include a description of the specific accommodation you are requesting as well as the job title and requisition number of the position for which you are applying.


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About General Motors

Sourced by ZipRecruiter

General Motors is a company with global scale and capabilities, headquartered in Detroit, Michigan, with employees around the world. The company employs over 165,000 people, serves six continents, operates across 22 time zones, and has a diverse workforce speaking 75 languages1. GM’s vision is to drive the world forward by pioneering innovations that move and connect people to what matters. The company is working towards an all-electric future with its new Ultium Platform and is pushing transportation options beyond our wildest imaginations with autonomous vehicles. GM is also committed to becoming the most inclusive company in the world.

Industry

Transportation equipment manufacturing

Company size

10,000+ Employees

Headquarters location

Detroit, MI, US

Year founded

1908