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Data Annotation Engineer Jobs in Michigan (NOW HIRING)

About You and The Role As an ML Training & Inference Infrastructure Engineer on the Data Platform ... Experience with annotation systems, dataset inspection tooling, or active-learning workflows. What ...

ML Infrastructure Engineer

Ann Arbor, MI Β· On-site

$160K - $250K/yr

Own and improve data pipelines that feed into the ML development loop. * Identify and mitigate ... Experience with annotation systems, dataset inspection tooling, or active-learning workflows. What ...

SAP ABAP Developer

Livonia, MI

$57.50 - $78/hr

... and performance-aware data models. Develop solutions using ABAP Cloud and ABAP for Cloud ... Build SAP Fiori and SAPUI5 applications, ideally using Fiori Elements and annotation-driven user ...

SAP ABAP Developer

Livonia, MI Β· On-site

$57.50 - $78/hr

Develop CDS data models, service definitions, custom handlers, authentication and authorization ... Build SAP Fiori and SAPUI5 applications, ideally using Fiori Elements and annotation-driven user ...

Use Ford Teamcenter/3DX to release and store 3D data, GD&T 3D Annotation & 2D drawings. * Ability ... engineered composites, TPEs, TPOs, and specialized extrusion and compression technologies.

Use Ford Teamcenter/3DX to release and store 3D data, GD amp;T 3D Annotation amp; 2D drawings ... engineered composites, TPEs, TPOs, and specialized extrusion and compression technologies.

Showing results 21-34

Data Annotation Engineer information

See Michigan salary details

$44.9K

$128.5K

$171.7K

How much do data annotation engineer jobs pay per year?

As of Sep 15, 2026, the average yearly pay for data annotation engineer in Michigan is $128,526.00, according to ZipRecruiter salary data. Most workers in this role earn between $73,200.00 and $170,800.00 per year, depending on experience, location, and employer.

What is a data annotation engineer?

A Data Annotation Engineer is responsible for labeling and annotating dataβ€”such as text, images, audio, or videoβ€”to train machine learning models. They ensure that data is accurately categorized and structured to improve model performance. This role often involves using specialized annotation tools, following detailed guidelines, and working closely with data scientists and AI teams. Data Annotation Engineers play a crucial role in the development of AI applications by providing high-quality labeled datasets for supervised learning.

What are the key skills and qualifications needed to thrive as a data annotation engineer?

To thrive as a Data Annotation Engineer, you need a strong background in data analysis, attention to detail, and familiarity with annotation processes, often supported by a degree in computer science or a related field. Proficiency with annotation tools like Labelbox, CVAT, or VIA, and understanding of data formats used in machine learning, is commonly required. Excellent communication, collaboration, and organizational skills help you effectively manage projects and cooperate with cross-functional teams. These abilities are crucial for delivering high-quality labeled data, which directly impacts the performance of AI and machine learning models.

What are the main challenges faced by data annotation engineers in their daily work?

One of the main challenges Data Annotation Engineers face is ensuring consistent accuracy and quality in labeling large and often complex datasets. Attention to detail is critical, as even small errors can significantly affect machine learning model performance. Additionally, engineers must frequently adapt to evolving annotation guidelines and emerging data types, which requires ongoing learning and flexibility. Collaboration with data scientists and project managers is common to clarify requirements and resolve ambiguities, making strong communication skills essential for success.

What is the salary of data annotation engineer?

The salary of a data annotation engineer typically ranges from $40,000 to $80,000 annually, depending on experience, location, and the complexity of annotation tasks. Entry-level positions may start lower, while experienced professionals with specialized skills in tools like Labelbox or CVAT can earn higher salaries.

What are popular job titles related to Data Annotation Engineer jobs in Michigan?

For Data Annotation Engineer jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Data Annotation Engineer jobs in Michigan look for?

The top searched job categories for Data Annotation Engineer jobs in Michigan are:

What cities in Michigan are hiring for Data Annotation Engineer jobs?

Cities in Michigan with the most Data Annotation Engineer job openings:

Infographic showing various Data Annotation Engineer job openings in Michigan as of September 2026, with employment types broken down into 56% Full Time, and 44% Contract. Highlights an 40% In-person, and 60% Remote job distribution, with an average salary of $128,526 per year, or $61.8 per hour.

Autonomy Droid Perception SWE - Offboard Systems

Ann Arbor, MI

$200K - $240K/yr

Full-time

Medical, Dental, Vision, PTO

Re-posted yesterday


Job description

About You and The Role

Zipline is operating the world's largest autonomous logistics network-delivering critical medical and commercial goods globally with high reliability, precision, and scale. As we expand into increasingly complex, safety-critical environments, the systems behind our autonomy stack must be robust, adaptable, and deeply integrated-especially at the intersection of perception and deployment. Our operational scale makes this a Physical AI opportunity like no other.

We're hiring Senior and Staff perception engineers to join our Droid team, the group responsible for the autonomy that powers Zipline's backyard delivery experience. This team owns the full stack of onboard, offboard and cloud-side perception systems that inform, validate, and augment our onboard autonomy. From generating rich 3D and semantic priors from aerial survey data to learning customer preferences and terrain features at scale, your work will define how we enable Zipline aircraft to scale mission-critical deliveries across complex, real-world environments.

This is not a purely research role-you'll be expected to move fast, ship production-grade systems, and find clever ways to apply state-of-the-art techniques to tangible, high-impact problems.

What You'll Do
  • Own the design and implementation of computer vision ML models that run in the cloud (or on our brand new on-prem GPU cluster!), helping us support and scale our on-device perception models.
  • Train and deploy large-scale models for semantic segmentation, feedforward 4D geometry, and learned preference modeling using aerial survey images, production deliveries and synthetic generated data.
  • Design and ship tools that predict deliverability, generate high-fidelity priors, and reduce the operational friction of onboarding new customers in new environments. You'll step in where our on-vehicle capabilities can't solve the problems we need to solve in order to scale the product.
  • Design evaluation and validation infrastructure to ensure models behave reliably in the field.
  • Zipline moves fast. On average, every 6 weeks, you will ship a new feature (or sometimes even a new model!) to production.
  • At the Senior level, you'll lead architectural decisions, drive experimentation, and help the team push the limits of what's possible with production-grade perception at scale. At the Staff level, you will own roadmapping the future of one or more offboard models in addition to the above.
What You'll Bring
  • At least 5+ years of experience (Senior) or 8+ years of experience (Staff) building and deploying deep learning-based perception systems, particularly in 3D geometry, semantic understanding, or mapping from remote sensing data.
  • Strong understanding of classical computer vision (e.g. camera calibration, epipolar geometry, structure-from-motion) and the ability to blend it with modern ML approaches such as feedforward multi-view models and gaussian splats
  • Hands-on experience training, fine-tuning, iterating on, and optimizing CNN, transformer and foundation-style model architectures in production environments.
  • An engineering mindset focused on outcomes over experimentation-you know how to prioritize what's good enough to ship now and what needs to be architected for scale later.
  • Familiarity with building training, data annotation, and evaluation pipelines-not just models.
  • Comfort working across systems: jumping into data pipelines, training infrastructure, or debugging distributed training issues as needed.
  • Experience deploying models in real-world, high-stakes robotics or autonomy applications is a strong plus for Senior and a requirement for Staff.
  • At the Staff level, we also expect to see experience bringing up new efforts within your role, and demonstrated examples of building staged roadmaps for challenging ML tasks.
What Else You Need To Know

The starting cash range for this role is $200,000 - $240,000 for Senior and $240,000 - $280,000 for Staff . Please note that this is a target, starting cash range for a candidate who meets the minimum qualifications for this role. The final cash pay for this role will depend on a variety of factors, including a specific candidate's experience, qualifications, skills, working location, and projected impact. The total compensation package for this role may also include: equity compensation; overtime pay; discretionary annual or performance bonuses; sales incentives; benefits such as medical, dental and vision insurance; paid time off; and more.
Zipline is an equal opportunity employer and prohibits discrimination and harassment of any type without regard to race, color, religion, age, sex, national origin, disability status, genetics, protected veteran status, sexual orientation, gender identity or expression, or any other characteristic protected by federal, state or local laws or our own sensibilities.

We value diversity at Zipline and welcome applications from those who are traditionally underrepresented in tech. If you like the sound of this position but are not sure if you are the perfect fit, please apply!