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Entry Level Machine Learning Engineer Jobs in Dearborn, MI

Varsity Tutors

Machine Learning Tutor

Ann Arbor, MI · Remote

$18 - $40/hr

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

Varsity Tutors

Machine Learning Tutor

Detroit, MI · Remote

$18 - $40/hr

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

Optimal Inc.

Robotics Software Engineer

Warren, MI · On-site

We are seeking a Robotics Engineer that has Embedded Software Engineering experience in designing ... Familiarity with robotics frameworks (ROS 2) and machine learning is a plus. Key Responsibilities

Optimal Inc.

Robotics Software Engineer

Warren, MI · On-site

We are seeking a Robotics Engineer that has Embedded Software Engineering experience in designing ... Familiarity with robotics frameworks (ROS 2) and machine learning is a plus. Key Responsibilities

THOMSON REUTERS

Lead Research Engineer

Ann Arbor, MI · On-site +1

$100K - $132K/yr

We hire engineers and specialists across a variety of AI research areas to drive the company ... Experienceintegrating Machine Learning solutionsinto production-grade softwarewith a sound ...

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Entry Level Machine Learning Engineer information

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$27.6K

$63.7K

$108.4K

How much do entry level machine learning engineer jobs pay per year?

As of Jul 14, 2026, the average yearly pay for entry level machine learning engineer in Dearborn, MI is $63,724.00, according to ZipRecruiter salary data. Most workers in this role earn between $47,300.00 and $72,100.00 per year, depending on experience, location, and employer.

What are the key skills and qualifications needed to thrive in the Entry Level Machine Learning Engineer position, and why are they important?

To thrive as an Entry Level Machine Learning Engineer, you need a solid understanding of machine learning algorithms, programming languages like Python, and a degree in computer science, engineering, or a related field. Familiarity with tools such as TensorFlow, PyTorch, scikit-learn, and version control systems like Git is highly valuable, and completing online courses or certifications can further demonstrate your skills. Strong analytical thinking, attention to detail, and effective communication are important soft skills in this role. These abilities are essential because they enable you to build accurate models, work collaboratively with teams, and communicate insights to stakeholders.

What are some typical projects or tasks an Entry Level Machine Learning Engineer might work on?

As an Entry Level Machine Learning Engineer, you’ll often work on tasks such as data preprocessing, feature engineering, and assisting in training and evaluating models under the guidance of senior engineers or data scientists. You may help develop prototypes, automate data collection pipelines, and collaborate with software engineers to integrate machine learning solutions into products. Working in this role typically involves frequent collaboration in a team environment, participating in code reviews, and learning best practices for scalable model deployment. These foundational experiences are designed to build your technical expertise and set the stage for future growth within the field.

What is an Entry Level Machine Learning Engineer job?

An Entry Level Machine Learning Engineer is responsible for developing, testing, and deploying machine learning models under the guidance of senior engineers. They work with datasets, implement algorithms, and optimize model performance. Their role often involves data preprocessing, feature engineering, and collaborating with data scientists and software engineers. Strong programming skills in Python, knowledge of ML frameworks like TensorFlow or PyTorch, and an understanding of statistics and algorithms are essential. This position serves as a foundation for building expertise in artificial intelligence and data-driven decision-making.

What are the most commonly searched types of Machine Learning Engineer jobs in Dearborn, MI? The most popular types of Machine Learning Engineer jobs in Dearborn, MI are:
What job categories do people searching Entry Level Machine Learning Engineer jobs in Dearborn, MI look for? The top searched job categories for Entry Level Machine Learning Engineer jobs in Dearborn, MI are:
What cities near Dearborn, MI are hiring for Entry Level Machine Learning Engineer jobs? Cities near Dearborn, MI with the most Entry Level Machine Learning Engineer job openings:
Entry Level Machine Learning Engineer jobs near you
Senior, Machine Learning Engineer - End-to-End

Senior, Machine Learning Engineer - End-to-End

Torc Robotics

Ann Arbor, MI • On-site, Remote

$119K - $158K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 21 days ago

Job description

About the Company
At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business.
A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family, we are focused solely on developing software for automated trucks to transform how the world moves freight.
Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.
Meet the Team:
As a Senior Machine Learning Engineer - End-to-End (E2E), you will develop and scale learning-based systems that connect multi-modal perception inputs to driving behavior, enabling safe, efficient, and human-like autonomy for real-world freight operations.
You'll work at the intersection of perception, prediction, and planning, contributing to unified learning pipelines that operate in closed-loop environments. This role focuses on owning meaningful portions of the E2E stack, improving model performance at scale, and driving iteration through data, experimentation, and cross-functional collaboration.
This is a hands-on engineering role focused on execution, iteration, and delivery.
What You'll Do
  • Own development and delivery of End-to-End ML models that map multi-modal sensor inputs (camera, LiDAR, radar, maps) to driving-relevant outputs (trajectories, cost functions, or intermediate representations)
  • Train and evaluate models using large-scale datasets from fleet logs, simulation, and synthetic data
  • Analyze model performance, identify failure modes, and drive data-driven improvements in robustness and generalization
  • Design and refine training pipelines, data workflows, and evaluation strategies to improve iteration speed and model quality
  • Contribute to model architecture decisions, including approaches such as imitation learning, reinforcement learning, transformers, and vision-language-action (VLA) models
  • Collaborate closely with Perception, Prediction, Planning, and Simulation teams to ensure alignment across the autonomy stack
  • Support integration of E2E models into simulation and on-vehicle systems for closed-loop validation
  • Improve tooling, experimentation workflows, and reproducibility across the team
  • Mentor junior engineers and contribute to team-level best practices and technical discussions

What You'll Need to Succeed
  • Bachelor's degree with 6+ years, Master's with 4+ years, or PhD with 0-2 years of experience in Machine Learning, Robotics, Computer Science, or a related field with a track record of publications in top-tier conferences (e.g., NeurIPS, ICML, ICLR, CVPR, ICCV, CoRL)
  • Experience developing and deploying ML models for autonomous systems, robotics, or complex decision-making environments
  • Strong programming skills in Python and PyTorch, with ability to write production-quality ML code
  • Experience training and evaluating models using large-scale datasets and distributed compute environments
  • Solid understanding of ML architectures used in E2E systems, such as Transformers, BEV models, VLA/VLM approaches, or diffusion models
  • Proven ability to debug model behavior, analyze performance metrics, and drive iterative improvements
  • Experience contributing to or influencing model architecture and training strategies
  • Ability to work cross-functionally and integrate ML systems into larger autonomy pipelines

Bonus Points
  • Experience developing End-to-End or mid-to-end models for autonomous driving or robotics
  • Experience with vision-language models (VLMs) or vision-language-action (VLA) systems
  • Familiarity with closed-loop simulation and evaluation frameworks
  • Experience with reinforcement learning or imitation learning in real-world systems
  • Experience with distributed training frameworks (e.g., Ray)
  • Understanding of vehicle dynamics, motion planning, or multi-agent systems

Work Location: For this position, we are open to hiring in Ann Arbor, MI (U.S.) office work locations in a hybrid capacity. We are also open to hiring Remote in the United States.
Perks of Being a Full-time Torc'r
Torc cares about our team members and we strive to provide benefits and resources to support their health, work/life balance, and future. Our culture is collaborative, energetic, and team focused. Torc offers:
  • A competitive compensation package that includes a bonus component and stock options
  • 100% paid medical, dental, and vision premiums for full-time employees
  • 401K plan with a 6% employer matchFlexibility in schedule and generous paid vacation (available immediately after start date)Company-wide holiday office closures
  • AD+D and Life Insurance

At Torc, we're committed to building a diverse and inclusive workplace. We celebrate the uniqueness of our Torc'rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities.
Even if you don't meet 100% of the qualifications listed for this opportunity, we encourage you to apply.
Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign-on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.
Job ID: 102665
Hiring Range for Job Opening
US Pay Range
$226,400-$271,700 USD

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