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Data Annotation Project Manager Jobs in Dearborn, MI

Data Center Project Manager

Livonia, MI ยท On-site

$113K/yr

Join our innovative team as a dynamic and detail-oriented Data Center Project Manager ! In this exciting role, you will oversee the entire lifecycle of data center projects, from startup to ...

... data-turn-id-container="request-WEB:42f7b233-ec2d-4f4d-845c-2838e5ce5bac-4" data-testid ... We are seeking a dynamic and organized Project Manager to oversee and coordinate projects from ...

NV5 is currently seeking a Project Manager to join our Americas Mission Critical team and service our clients nationally as needs dictate. The successful candidate will be self-motivated and well ...

Project and Program Management MRM is part of the Omnicom Precision Marketing activation practice ... This practice integrates CRM platform expertise, journey management, and first-party data ...

Project and Program Management MRM is part of theOmnicomPrecision Marketing activation practice ... This practice integrates CRM platform expertise, journey management, and first-party data ...

Project and Program Management MRM is part of theOmnicomPrecision Marketing activation practice ... This practice integrates CRM platform expertise, journey management, and first-party data ...

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Data Annotation Project Manager information

See Dearborn, MI salary details

$15

$52

$73

How much do data annotation project manager jobs pay per hour?

As of Aug 28, 2026, the average hourly pay for data annotation project manager in Dearborn, MI is $52.83, according to ZipRecruiter salary data. Most workers in this role earn between $45.72 and $61.83 per hour, depending on experience, location, and employer.

What is a data annotation project manager?

A Data Annotation Project Manager is responsible for overseeing projects that involve labeling and categorizing data, such as images, text, or audio, to train machine learning models. They coordinate teams of annotators, manage project timelines, and ensure the quality and accuracy of the annotated data. This role often acts as a bridge between data scientists, clients, and annotation teams, ensuring project requirements are met efficiently and effectively.

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

To thrive as a Data Annotation Project Manager, you need strong project management skills, a solid understanding of data annotation processes, and experience with quality assurance, often supported by a degree in a relevant field. Familiarity with annotation tools (like Labelbox or Supervisely), workflow management platforms, and sometimes agile or PMP certification is highly beneficial. Exceptional communication, attention to detail, and leadership abilities help you effectively coordinate teams and ensure project deliverables meet quality standards. These skills are essential for managing complex annotation projects efficiently, maintaining data integrity, and supporting successful machine learning outcomes.

What are some common challenges faced by data annotation project managers, and how can they be managed effectively?

One of the primary challenges Data Annotation Project Managers face is ensuring high-quality, consistent labeling across large and sometimes distributed annotation teams. Managing tight deadlines while maintaining annotation accuracy requires effective training, clear guidelines, and regular quality checks. Additionally, balancing communication between data scientists, clients, and annotators is crucial to align expectations and resolve ambiguities quickly. Successful managers often implement robust feedback loops, leverage annotation tools with built-in quality control features, and foster an open environment for continuous improvement.

What is the difference between Data Annotation Project Manager vs Data Labeling Specialist?

AspectData Annotation Project ManagerData Labeling Specialist
CredentialsTypically requires project management experience, certifications in data management or related fieldsOften requires basic technical skills, familiarity with labeling tools, sometimes certifications in data annotation
Work EnvironmentOversees teams, manages projects, coordinates workflows in office or remote settingsPerforms labeling tasks, often in a remote or on-site environment, focused on data tagging
Employer & Industry UsageUsed by tech companies, AI firms, and data service providers for managing annotation projectsEmployed within similar industries, focusing on executing labeling tasks under supervision

The main difference is that the Data Annotation Project Manager oversees and coordinates annotation projects, ensuring quality and deadlines, while the Data Labeling Specialist focuses on executing the labeling tasks themselves. Both roles are essential in the data annotation process but differ in responsibilities and scope.

What job categories do people searching Data Annotation Project Manager jobs in Dearborn, MI look for?

The top searched job categories for Data Annotation Project Manager jobs in Dearborn, MI are:

What cities near Dearborn, MI are hiring for Data Annotation Project Manager jobs?

Cities near Dearborn, MI with the most Data Annotation Project Manager job openings:

Infographic showing various Data Annotation Project Manager job openings in Dearborn, MI as of August 2026, with employment types broken down into 85% Full Time, 14% Part Time, and 1% Contract. Highlights an 84% Physical, 3% Hybrid, and 13% Remote job distribution, with an average salary of $109,893 per year, or $52.8 per hour.

Software Engineer II - Fleet Enablement & Insights (Annotation Platform)

Torc Robotics

Ann Arbor, MI โ€ข On-site

$95K - $130K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 13 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
The Software Engineer II will be a core member of the Fleet Enablement & Insights team, building Torc's in-house annotation platform: the web-based tooling that turns multi-sensor autonomy data into the labeled datasets that train and validate the autonomous truck platform. This role develops the interactive 2D/3D annotation editor and the services behind it which fuses HD map data and multi-camera, lidar, and other sensor context into the labeling workflow. The platform also serves adjacent use cases across the data organization, including data QC and scene-selection review. The ideal candidate is a collaborative engineer who thrives in a fast-paced environment and is passionate about high-performance visualization of large sensor datasets, thoughtful annotator-facing UX, and the pipelines that connect human review to machine learning at scale. This position offers the opportunity to work at the intersection of software engineering, computer graphics, and machine learning with a direct line of sight to the data that trains and validates the AV stack.
What You'll Do
  • Design, develop, and maintain the TypeScript/React web application for 2D and 3D annotation, including cuboid and polygon editing, cross-frame interpolation and track propagation, attribute editing, and review-first (accept/reject) workflows.
  • Build high-performance point cloud and image rendering with three.js/WebGL: octree/LOD-based streaming formats, predictive prefetching for smooth frame scrubbing, camera-LiDAR projection, and multi-sensor overlays across a high camera count.
  • Design and build the services behind the editor: label storage and versioning, task assignment and QA workflow, authentication, and multi-user isolation guardrails.
  • Integrate pre-labeling and pseudo-labeling pipeline outputs into the annotation workflow, and instrument acceptance-rate and throughput metrics that drive the auto-labeling feedback loop.
  • Fuse HD map data into annotation and QC workflows as priors and reference layers for labeling and validation.
  • Build data converters and ingestion paths from Torc's multi-sensor scene data (multiple LiDARs, many cameras, calibration data) into the platform's formats.
  • Deliver dataset exports compatible with downstream ML training and validation consumers, with the lineage and auditability the safety case requires.
  • Leverage AWS cloud services and Databricks adjacency to host scene data and deploy scalable, reliable services.
  • Collaborate closely with the Data Annotation team (the platform's primary users), Autonomy/ML, Scene Selection, Mapping, and Data Engineering to align the tool with real annotator workflows and downstream requirements.
  • Participate in agile ceremonies, sprint planning, and weekly demos with annotators and stakeholders to keep the tool grounded in real use.
  • Contribute to a culture of engineering excellence through code reviews, documentation, and knowledge sharing, including hardening prototype code into production systems.
  • Identify and address technical debt, performance bottlenecks, and reliability gaps across the annotation platform.

What You'll Need to Succeed
  • Strong proficiency in TypeScript and React, with experience building and shipping production-quality web applications.
  • Experience with browser-based 3D graphics (three.js, WebGL, or similar), or strong graphics fundamentals and a demonstrated ability to ramp quickly.
  • Proficiency in Python for building production backend services and APIs.
  • Experience working with large binary or sensor datasets (point clouds, imagery, video) and optimizing data-heavy user interfaces for performance.
  • Strong proficiency with SQL and hands-on experience with PostgreSQL for label, task, and metadata storage.
  • Experience with AWS services for hosting data and deploying services.
  • Proficiency with Git and GitHub for version control, branching strategies, and collaborative code workflows.
  • Familiarity with JIRA or similar project management tools for tracking tasks, bugs, and sprint deliverables.
  • Solid understanding of software engineering fundamentals including data structures, algorithms, and system design.
  • Strong written and verbal communication skills with the ability to effectively collaborate across technical and non-technical stakeholders, including non-engineer users of the tools you build.
  • Bachelor's Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 4+ years of experience or;
  • Master's Degree in Computer Science, Robotics, Electrical Engineering or related technical field plus demonstrates competences and technical proficiencies typically acquired through 0-3+ years of experience.

Bonus Points
  • Experience with point cloud rendering and streaming formats (octree/LOD structures such as Potree or COPC, 3D Tiles, LAS/LAZ) or large-scale spatial data structures.
  • Experience building or extending annotation/labeling tools.
  • Familiarity with robotics data and visualization ecosystems (e.g., Rerun, Foxglove, MCAP, ROS bags).
  • Background in machine learning workflows for perception: object detection, tracking, segmentation, model-assisted or auto-labeling, active learning.
  • Understanding of multi-view geometry and sensor calibration (camera intrinsics/extrinsics, LiDAR-camera projection, time synchronization).
  • Prior experience working with High-Definition (HD) maps, map formats (e.g., OpenDRIVE, NDS, Lanelet2), or fusing map data into perception or labeling workflows.
  • Familiarity with PostGIS or spatial queries for geometry operations and geospatial data management.
  • Experience with Databricks or similar platforms for large-scale data processing.
  • Contributions to open-source graphics, geospatial, annotation, or data engineering projects.

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 match
  • Flexibility in schedule and generous paid vacation (available immediately after start date)
  • 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: 102797
Hiring Range for Job Opening
US Pay Range
$139,000-$166,800 USD