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Freelance Machine Learning Data Annotation Jobs in Massachusetts

As a Machine Learning Engineer on the Data Mining team, your mission is to help build the "Brain" of this engine. You will work with state-of-the-art foundation models to extract insights from ...

As a Machine Learning Engineer on the Data Mining team, your mission is to help build the "Brain" of this engine. You will work with state-of-the-art foundation models to extract insights from ...

The role involves ownership of technical decisions for building and deploying state-of-the-art machine learning models, requiring a strong background in data engineering and model training.

Machine Learning Tutor

Lowell, MA · Remote

$18 - $40/hr

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Lynn, MA · Remote

$18 - $40/hr

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Newton, MA · Remote

$18 - $40/hr

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Quincy, MA · Remote

$18 - $40/hr

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Waltham, MA · Remote

$18 - $40/hr

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Machine Learning Tutor

Boston, MA · Remote

$18 - $40/hr

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Guides students through data preprocessing, feature selection, building and comparing ... Familiar with machine learning curricula and common challenges such as understanding bias-variance ...

Senior Machine Learning Engineer

Boston, MA · On-site +1

$133K - $175K/yr

Data Preprocessing: Clean, transform, and prepare large, complex healthcare datasets for machine learning model development. This includes handling missing values, outlier detection, feature ...

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Freelance Machine Learning Data Annotation information

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.

What are the key skills and qualifications needed to thrive as a Freelance Machine Learning Data Annotation specialist, and why are they important?

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 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 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 are the most commonly searched types of Machine Learning Data Annotation jobs in Massachusetts? The most popular types of Machine Learning Data Annotation jobs in Massachusetts are:
What are popular job titles related to Freelance Machine Learning Data Annotation jobs in Massachusetts? For Freelance Machine Learning Data Annotation jobs in Massachusetts, the most frequently searched job titles are:
What job categories do people searching Freelance Machine Learning Data Annotation jobs in Massachusetts look for? The top searched job categories for Freelance Machine Learning Data Annotation jobs in Massachusetts are:
What cities in Massachusetts are hiring for Freelance Machine Learning Data Annotation jobs? Cities in Massachusetts with the most Freelance Machine Learning Data Annotation job openings:
Machine Learning Engineer, Data Mining

Machine Learning Engineer, Data Mining

Motional

Boston, MA • On-site, Remote

$144K - $192K/yr

Full-time

Medical, Dental, Vision, Life, Retirement

Posted 23 days ago


Job description

Mission Summary:
At Motional, we're transforming how autonomous vehicles discover critical intelligence hidden within petabytes of multimodal sensor data. Our next-generation autonomous driving stack depends on finding the rare edge cases, long-tail scenarios, and model errors that matter most. Omnitag, our ML-powered multimodal data mining framework, is the engine that powers this discovery.
As a Machine Learning Engineer on the Data Mining team, your mission is to help build the "Brain" of this engine. You will work with state-of-the-art foundation models to extract insights from Motional's driving data, working at the intersection of large-scale representation learning and data retrieval. By building smarter mining tools and efficient data pipelines, you will accelerate the model improvement lifecycle for teams working on post-training analysis, error diagnosis, and dataset curation.
What You'll Do:
  • Build and Train ML Pipelines: Develop, train, and fine-tune machine learning models for multimodal sensor data (e.g., vision, LiDAR). Focus on implementing supervised and self-supervised learning approaches to improve data search and retrieval.
  • Support Model Deployment: Implement scalable data preprocessing and augmentation pipelines. Assist in applying standard optimization techniques (e.g., batch inference, quantization) to ensure models run efficiently in production environments.
  • Data Mining & Analysis: Help develop embedding-based search tools and "active learning" workflows to identify critical driving scenarios.
  • Monitor Production Performance: Help build and maintain dashboards to monitor model health, data drift, and system performance. Identify regressions and assist in the operational support of our data mining services.
  • Learn and Apply Best Practices: Follow software engineering standards (version control, CI/CD, unit testing) for ML code. Participate in code reviews and contribute to technical documentation.
  • Collaborate Across Teams: Work closely with senior engineers and machine learning engineers to translate model prototypes into maintainable, scalable engineering solutions.

What We're Looking For (Must-Haves):
  • BS or MS in Computer Science, Machine Learning, or a related field.
  • Hands-on experience with PyTorch (preferred) or TensorFlow/JAX. You should be comfortable training models and evaluating them using standard metrics.
  • Strong proficiency in Python with the ability to write clean, modular, and well-documented code.
  • Working knowledge of version control, unit testing, and basic software design patterns.
  • Experience working with large datasets, including proficiency in SQL and data libraries like Pandas and NumPy.
  • A solid grasp of the full ML lifecycle, from data cleaning and feature engineering to validation and deployment basics.
  • A proactive learner who thrives on constructive feedback and is eager to grow within a high-stakes engineering environment.

Bonus Points (Nice-to-Haves):
  • MS/PhD in Computer Science, Machine Learning, or related field.
  • Experience with agentic systems, autonomous reasoning, chain-of-thought models, or LLM-based planning.
  • Background in autonomous driving, robotics, or real-time decision-making systems.
  • Familiarity with multimodal learning, sensor fusion, or embodied AI.
  • Experience building active learning loops, using the model to find the data that breaks the model.
  • Experience with ML-based data mining, active learning, or contrastive learning.
  • Knowledge of model serving tools (TF Serving, Triton, TorchServe) and MLOps platforms.
  • Publication in top-tier conferences (e.g., ICCV, CVPR, ECCV)

We encourage a hybrid schedule with in-office time at one of our locations in Boston, Pittsburgh, or Las Vegas to support collaboration, or this role can be fully remote.
The salary range for this role is an estimate based on a wide range of compensation factors including but not limited to specific skills, experience and expertise, role location, certifications, licenses, and business needs. The estimated compensation range listed in this job posting reflects base salary only. This role may include additional forms of compensation such as a bonus or company equity. The recruiter assigned to this role can share more information about the specific compensation and benefit details associated with this role during the hiring process.
Candidates for certain positions are eligible to participate in Motional's benefits program. Motional's benefits include but are not limited to medical, dental, vision, 401k with a company match, health saving accounts, life insurance, pet insurance, and more.
Salary Range
$144,000-$192,000 USD
Motional is a driverless technology company making autonomous vehicles a safe, reliable, and accessible reality. We're driven by something more.
Our journey is always people first.
We aren't just developing driverless cars; we're creating safer roadways, more equitable transportation options, and making our communities better places to live, work, and connect. Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a technology with the potential to transform the way we move.
Higher purpose, greater impact.
We're creating first-of-its-kind technology that will transform transportation. To do so successfully, we must design for everyone in our cities and on our roads. We believe in building a great place to work through a progressive, global culture that is diverse, inclusive, and ensures people feel valued at every level of the organization. Diversity helps us to see the world differently; it's not only good for our business, it's the right thing to do.
Scale up, not starting up.
Our team is behind some of the industry's largest leaps forward, including the first fully-autonomous cross-country drive in the U.S, the launch of the world's first robotaxi pilot, and operation of the world's longest-standing public robotaxi fleet. We're driven to scale; we're moving towards commercialization of our technology, and we need team members who are ready to embrace change and challenges.
Formed as a joint venture between Hyundai Motor Group and Aptiv, Motional is fundamentally changing how people move through their lives. Headquartered in Boston, Motional has operations in the U.S and Asia. For more information, visit www.Motional.com and follow us on Twitter, LinkedIn, Instagram and YouTube.
Motional AD Inc. is an EOE. We celebrate diversity and are committed to creating an inclusive environment for all employees. To comply with Federal Law, we participate in E-Verify. All newly-hired employees are queried through this electronic system established by the DHS and the SSA to verify their identity and employment eligibility.