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Freelance Machine Learning Data Annotation Jobs in Michigan

Corning

You will partner with data scientists, analytics leaders, IT, and manufacturing teams to move ... machine learning pipelines, including data ingestion, preprocessing, training, validation ...

Saanvi Technologies

Machine Learning Engineer 3

Dearborn, MI · On-site

$105K - $126K/yr

Machine Learning Engineering Engineer 3 Dearborn, MI W2 Position Description: We are seeking an ... This role combines expertise in Data Science, Software Engineering, and MLOps to deliver scalable ...

FastTek

Machine Learning Engineer

Dearborn, MI

Machine Learning Engineer #1058742 Position Description: We are seeking an experienced AI Engineer ... This role combines expertise in Data Science, Software Engineering, and MLOps to deliver scalable ...

Stefanini

Machine Learning Engineer

Allen Park, MI · On-site

Stefanini is looking for a Machine Learning Engineer(Allen Park, MI) For quick apply, please reach ... AIPGEE, Advance data Migration, API, Data Management Experience Required:5+ years of experience in ...

Stellantis

Machine Learning Engineer

Auburn Hills, MI · On-site

$108K - $130K/yr

We are looking for a Machine Learning Engineer / Data Scientist to develop advanced statistical models and simulations that drive Vehicle Configuration Optimization (VCO) . This role will leverage ...

Mariana Minerals

Machine Learning Engineer

Ann Arbor, MI · On-site

$120K - $180K/yr

... data-driven decision-making. The Role Mariana Minerals is building the critical minerals supply ... As a Machine Learning Engineer at Mariana, you'll help build and improve the machine learning ...

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Freelance Machine Learning Data Annotation information

What is freelance machine learning data annotation?

Freelance machine learning data annotation involves labeling or tagging data—such as images, text, audio, or video—to help train machine learning models. As a freelancer, you work independently or through platforms, completing specific annotation tasks assigned by companies or researchers. This work is essential because high-quality labeled data is required for AI systems to learn and make accurate predictions. Annotators may categorize images, transcribe speech, or highlight relevant information in documents. The flexibility of freelancing allows you to choose projects and work remotely.

What are the key skills and qualifications needed to thrive as a freelance machine learning data annotation specialist?

To thrive as a Freelance Machine Learning Data Annotation specialist, you need attention to detail, basic knowledge of data labeling concepts, and familiarity with machine learning data types. Experience with annotation tools (such as Labelbox, RectLabel, or CVAT) and understanding of data privacy protocols are commonly required. Strong communication, time management, and the ability to follow complex guidelines are essential soft skills for delivering accurate results. These skills ensure high-quality, consistent data annotation, which is critical for effective machine learning model training and performance.

What are some common challenges faced by freelance machine learning data annotators, and how can they be managed?

Freelance machine learning data annotators often encounter challenges such as maintaining data accuracy, handling repetitive tasks, and understanding complex annotation guidelines. Staying organized and regularly reviewing project instructions can help ensure consistency and quality in annotations. Additionally, communicating proactively with project managers and utilizing annotation tools efficiently can help manage workload and clarify uncertainties. Building expertise in different data types (text, image, audio) also allows annotators to diversify their projects and reduce monotony.

What is the difference between Freelance Machine Learning Data Annotation vs Data Labeler?

AspectFreelance Machine Learning Data AnnotationData Labeler
CredentialsBasic understanding of annotation tools, sometimes with specialized domain knowledgeTypically no formal credentials required
Work EnvironmentRemote, flexible, project-basedOften remote or in-house, depending on employer
Industry UsageUsed in AI/ML development for training datasetsUsed in data preparation for various industries, including AI
Search/Comparison IntentFocuses on freelance opportunities, project scope, and toolsMore general, often employed by companies for data labeling tasks

Freelance Machine Learning Data Annotation involves independently completing annotation tasks for AI models, often with specialized tools and domain knowledge. Data Labelers typically perform similar tasks but may work as employees or contractors within a company. The main difference lies in the freelance nature and project-based work of data annotation roles.

Can I work for freelance machine learning data annotation with no experience?

Freelance machine learning data annotation jobs often do not require prior experience, as many tasks involve simple labeling or categorization that can be learned quickly. Basic computer skills, attention to detail, and familiarity with annotation tools are helpful, and training is usually provided. However, building a portfolio or gaining some familiarity with data annotation platforms can improve job prospects.

What are popular job titles related to Freelance Machine Learning Data Annotation jobs in Michigan?

For Freelance Machine Learning Data Annotation jobs in Michigan, the most frequently searched job titles are:

What job categories do people searching Freelance Machine Learning Data Annotation jobs in Michigan look for?

The top searched job categories for Freelance Machine Learning Data Annotation jobs in Michigan are:

What cities in Michigan are hiring for Freelance Machine Learning Data Annotation jobs?

Cities in Michigan with the most Freelance Machine Learning Data Annotation job openings:

Freelance Machine Learning Data Annotation jobs near you
Infographic showing various Freelance Machine Learning Data Annotation job openings in Michigan as of June 2026, with employment types broken down into 78% Full Time, and 22% Contract. Highlights an 94% In-person, and 6% Remote job distribution.

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

Torc Robotics

Ann Arbor, MI • On-site

$95K - $130K/yr

Full-time

Medical, Dental, Vision, Life, Retirement, PTO

Posted 5 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, Software Engineering, or a related technical field or equivalent 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

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