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Machine Learning Engineer Jobs in Detroit, MI (NOW HIRING)

Senior Machine Learning Test Engineer

Novi, MI · On-site +1

$103.70K - $134.60K/yr

Job Requisition ID # 26WD98377 Senior Machine Learning Test Engineer Location: United States East Coast Position Overview As a Senior Machine Learning Test Engineer in the Research Enablement team ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Deep knowledge of supervised learning, unsupervised learning, feature engineering, model selection ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Certifications in artificial intelligence, machine learning, or cloud platforms, such as AWS Certified Machine Learning - Specialty, Google Cloud Professional Machine Learning Engineer, Microsoft ...

... machine learning models and large language models. • Conduct research to provide technical ... & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot ...

Your mission, roles and responsibilities Role Summary As a Data Scientist / Machine Learning Engineer, you will be an integral part of our team, playing a pivotal role in leveraging data-driven ...

... machine learning models and large language models. • Conduct research to provide technical ... & DevOps teams, Data scientists, Machine Learning & GenAI Engineers, and Business teams to pilot ...

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Machine Learning Engineer information

See Detroit, MI salary details

$28.8K

$117.8K

$177.1K

How much do machine learning engineer jobs pay per year?

As of May 29, 2026, the average yearly pay for machine learning engineer in Detroit, MI is $117,823.00, according to ZipRecruiter salary data. Most workers in this role earn between $92,900.00 and $141,800.00 per year, depending on experience, location, and employer.

What Does a Machine Learning Engineer Do?

A machine learning engineer maintains production systems and often works with other engineers. In this career, you work with software development methodology, use modern software development tools, and use agile practices. You also play a role in software design and architecture, so you may occasionally work with a programmer. An engineer may help to predict how a model should perform or seek out regression issues by using different test types and algorithms. To fulfill your duties and responsibilities, you work on a computer and use an array of skills and programs to carry out these tests.

What are the key skills and qualifications needed to thrive as a Machine Learning Engineer, and why are they important?

To thrive as a Machine Learning Engineer, you need strong programming skills (particularly in Python), a solid background in mathematics and statistics, and a degree in computer science or a related field. Experience with machine learning frameworks (such as TensorFlow or PyTorch), data processing tools, and cloud platforms is typically required. Problem-solving ability, effective communication, and adaptability are crucial soft skills for collaborating with teams and translating complex models into practical solutions. These competencies ensure the development, deployment, and continual improvement of machine learning systems that drive business value.

What are some common challenges faced by Machine Learning Engineers when deploying models to production?

Machine Learning Engineers often encounter challenges such as ensuring model scalability, maintaining data consistency between training and production environments, and monitoring model performance over time. Integrating models into existing software infrastructure may require collaboration with DevOps and software engineering teams to address issues like latency, version control, and resource allocation. Additionally, ongoing model maintenance is crucial to prevent model drift and ensure that predictions remain accurate as new data becomes available.

What are Machine Learning Engineers?

Machine Learning Engineers are specialized software engineers who design, build, and deploy machine learning models and systems. They work at the intersection of software engineering and data science, transforming data-driven prototypes into scalable, production-ready solutions. Their responsibilities include data preprocessing, model selection, algorithm implementation, and optimizing models for performance and efficiency. Machine Learning Engineers often collaborate with data scientists, software developers, and other stakeholders to integrate AI technologies into products and services.

What jobs make $3,000 a month without a degree?

A Machine Learning Engineer typically requires a degree, but roles such as data annotator, technical support specialist, or freelance programmer can sometimes earn around $3,000 monthly without a formal degree, especially with relevant skills and experience. These jobs often involve self-taught skills, online certifications, or on-the-job training and may require proficiency in tools like Python or cloud platforms.

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

AspectMachine Learning EngineerData Scientist
CredentialsBachelor's or Master's in CS, Data Science, or related; experience with ML frameworksBachelor's or Master's in Statistics, Data Science, or related; strong analytical skills
Work EnvironmentDevelops scalable ML models, deploys algorithms into productionAnalyzes data, builds models, interprets data insights
Industry UsageTech companies, startups, AI-focused firmsFinance, healthcare, marketing, research organizations

While both roles work with data and machine learning, Machine Learning Engineers focus on building and deploying scalable ML models in production environments. Data Scientists primarily analyze data, create models, and generate insights. The roles often overlap but differ in their core responsibilities and focus areas.

What are the most commonly searched types of Machine Learning Engineer jobs in Detroit, MI? The most popular types of Machine Learning Engineer jobs in Detroit, MI are:
What are popular job titles related to Machine Learning Engineer jobs in Detroit, MI? For Machine Learning Engineer jobs in Detroit, MI, the most frequently searched job titles are:
What cities near Detroit, MI are hiring for Machine Learning Engineer jobs? Cities near Detroit, MI with the most Machine Learning Engineer job openings:
Senior Principal Machine Learning Engineer, ML Platform and Systems Architecture

Senior Principal Machine Learning Engineer, ML Platform and Systems Architecture

Autodesk

Novi, MI • Remote

Full-time

Posted 25 days ago


Autodesk rating

9.5

Company rating: 9.5 out of 10

Based on 5 frontline employees who took The Breakroom Quiz

5th of 183 rated software companies


Job description

Job Requisition ID #

26WD94803Senior Principal Machine Learning Engineer, ML Platform and Systems ArchitecturePosition Overview

The work we do at Autodesk touches nearly every person on the planet. By creating software tools for making buildings, machines, and even the latest movies, we influence and empower some of the most creative people in the world to solve problems that matter.

Autodesk is seeking a Senior Principal ML Engineer, ML Platform and Systems Architecture to define and drive the technical strategy for large-scale machine learning platforms and systems. This is a top-level engineering leadership role for a technical authority who can shape multi-year architecture, influence engineering standards across teams, and lead major platform initiatives that connect research, product, and business goals.

You will be responsible for driving the evolution of the systems that enable machine learning across Autodesk, including training infrastructure, data platforms, evaluation and experimentation systems, model serving frameworks, and operational excellence for production ML. You will work across organizational boundaries to guide decisions, resolve hard technical challenges, and ensure that platform investments are aligned with long-term product and business outcomes.

This role is fully remote-friendly, with team members distributed across the US and Canada.

Location: US or Canada Remote

Responsibilities
  • Define and lead technical strategy for a domain or large-scale platform supporting machine learning systems
  • Drive architecture decisions across teams for scalable training, data, evaluation, deployment, observability, and reliability systems
  • Lead multi-team initiatives with far-reaching technical impact across a function, platform, or division
  • Define technical direction for data pipelines that support large-scale structured and semi-structured technical datasets
  • Set standards for data lineage, provenance, governance, and responsible data usage in ML systems
  • Lead architecture for distributed data processing and orchestration systems such as Ray, Airflow, Spark, or similar platforms
  • Define scalable approaches for model deployment, inference services, monitoring, and observability for production ML systems
  • Influence platform direction for ML-ready representations of geometry, graph, hierarchical, or multimodal data
  • Influence standards for engineering quality, architecture, resiliency, risk management, and operational excellence
  • Identify long-term technical and operational risks and guide investment decisions that future-proof platform capabilities
  • Serve as a technical authority and trusted advisor to engineering leaders, senior engineers, and cross-functional stakeholders
  • Resolve complex cross-team technical problems by framing options, aligning stakeholders, and driving execution
  • Champion engineering practices that improve service quality, release readiness, monitoring, incident response, and maintainability
  • Mentor senior engineers and help build the next level of technical leadership within the organization
  • Clearly articulate the business rationale for technical investments and ensure alignment with broader organizational goals
Minimum Qualifications
  • Bachelor's or Master's degree in Computer Science, Engineering, or a related field, or equivalent industry experience
  • At least 8 years of industry experience in software engineering, ML platform architecture, distributed systems, or related domains, including experience driving architecture, cross-team technical direction, and large-scale platform outcomes
  • Significant experience in software architecture, distributed systems, platform engineering, or ML infrastructure at scale
  • Deep expertise in one or more critical areas such as distributed training, data platforms, ML platform architecture, model serving, or reliability engineering
  • Proven record of leading technical strategy and delivering cross-team outcomes with broad organizational impact
  • Strong command of cloud-native architectures, production engineering practices, and large-scale system design
  • Demonstrated ability to influence architecture and engineering standards beyond a single team
  • Strong executive-level communication and the ability to connect technical direction to business priorities
Preferred Qualifications
  • Experience setting architecture direction for ML platforms used across multiple teams or organizations
  • Experience building or scaling data pipelines for large-scale structured and semi-structured technical datasets
  • Experience with data lineage, provenance, governance, and responsible data usage in ML systems
  • Experience with distributed data processing and orchestration systems such as Ray, Airflow, Spark, or similar platforms
  • Experience with model deployment, inference services, monitoring, and observability for production ML systems
  • Experience building ML-ready representations for geometry, graph, hierarchical, or multimodal data
  • Experience building or scaling foundation model infrastructure and high-throughput data systems
  • Experience leading engineering improvements around resiliency, service reviews, fire drills, and risk reduction
  • Familiarity with AEC, design technology, BIM/CAD ecosystems, or Autodesk products
  • External technical leadership through architecture leadership, speaking, or domain expertise is a plus
The Ideal Candidate
  • Is a deeply technical leader who still operates effectively in hands-on engineering contexts
  • Thinks in systems, platforms, and multi-year strategy
  • Leads through influence, judgment, and clarity
  • Builds alignment across teams while holding a high bar for technical excellence

Learn More

About Autodesk

Welcome to Autodesk! Amazing things are created every day with our software - from the greenest buildings and cleanest cars to the smartest factories and biggest hit movies. We help innovators turn their ideas into reality, transforming not only how things are made, but what can be made.

We take great pride in our culture here at Autodesk - it's at the core of everything we do. Our culture guides the way we work and treat each other, informs how we connect with customers and partners, and defines how we show up in the world.

When you're an Autodesker, you can do meaningful work that helps build a better world designed and made for all. Ready to shape the world and your future? Join us!

Benefits

From health and financial benefits to time away and everyday wellness, we give Autodeskers the best, so they can do their best work. Learn more about our benefits in the U.S. by visiting https://benefits.autodesk.com/

Salary transparency

Salary is one part of Autodesk's competitive compensation package. For U.S.-based roles, we expect a starting base salary between $178,875 and $320,650. Offers are based on the candidate's experience and geographic location, and may exceed this range. In addition to base salaries, our compensation package may include annual cash bonuses, commissions for sales roles, stock grants, and a comprehensive benefits package.

Equal Employment Opportunity

At Autodesk, we're building a diverse workplace and an inclusive culture to give more people the chance to imagine, design, and make a better world. Autodesk is proud to be an equal opportunity employer and considers all qualified applicants for employment without regard to race, color, religion, age, sex, sexual orientation, gender, gender identity, national origin, disability, veteran status or any other legally protected characteristic. We also consider for employment all qualified applicants regardless of criminal histories, consistent with applicable law.

Diversity & Belonging

We take pride in cultivating a culture of belonging where everyone can thrive. Learn more here: https://www.autodesk.com/company/diversity-and-belonging

Are you an existing contractor or consultant with Autodesk?

Please search for open jobs and apply internally (not on this external site).


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About Autodesk

Sourced by ZipRecruiter

Autodesk is changing how the world is designed and made. Our technology spans architecture, engineering, construction, product design, manufacturing, media, and entertainment, empowering innovators everywhere to solve challenges big and small. From greener buildings to smarter products to more mesmerizing blockbusters, Autodesk software helps our customers to design and make a better world for all. For more information visit autodesk.com or follow @autodesk.

Industry

Software development

Company size

10,000+ Employees

Headquarters location

San Rafael, CA, US

Year founded

1982