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Data Annotation Research Jobs in Boston, MA (NOW HIRING)

FieldAI

Senior Data Operations Engineer

Boston, MA

$110K - $140K/yr

Data annotation for robotics or autonomous vehicles * QA for hardware and/or software * 3D scanning and 3D printing * Data collection and human subjects research (IRB/consent familiarity a plus) * AR ...

FieldAI

Senior Data Operations Engineer

Boston, MA · On-site

$110K - $140K/yr

Data annotation for robotics or autonomous vehicles * QA for hardware and/or software * 3D scanning and 3D printing * Data collection and human subjects research (IRB/consent familiarity a plus) * AR ...

FieldAI

Senior Data Operations Engineer

Boston, MA

$110K - $140K/yr

Data annotation for robotics or autonomous vehicles * QA for hardware and/or software * 3D scanning and 3D printing * Data collection and human subjects research (IRB/consent familiarity a plus) * AR ...

Vrtx

Pathology Research Scientist

Boston, MA

$105K - $158K/yr

Pathobiology Research Scientist will perform routine and specialized histology techniques, wet lab ... Knowledge and experience with image review, annotation, and visual data analysis using image ...

Motional

Staff Front End Engineer

Boston, MA · On-site +1

$172K - $229K/yr

Collaborate closely with ML, frontend, UX, data services, data mining, and data annotation teams to ... Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a ...

Motional

Staff Front End Engineer

Boston, MA · On-site +1

$172K - $229K/yr

Collaborate closely with ML, frontend, UX, data services, data mining, and data annotation teams to ... Our team is made up of engineers, researchers, innovators, dreamers and doers, who are creating a ...

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All JobsData Annotation Research JobsData Annotation Research Jobs in Boston, MA

Data Annotation Research information

What qualifications do I need for data annotation?

Data annotation research roles typically require basic computer skills, attention to detail, and familiarity with annotation tools or platforms. A high school diploma or equivalent is usually sufficient, though some positions may prefer experience with data labeling, machine learning concepts, or specific software. Strong communication skills and the ability to work independently are also beneficial.

What are some common challenges faced in Data Annotation Research roles, and how can they be addressed?

Professionals in Data Annotation Research often encounter challenges such as maintaining consistency in labeling, dealing with ambiguous data, and managing large datasets efficiently. These issues can be addressed by following detailed annotation guidelines, participating in regular calibration sessions with the team, and utilizing annotation tools that support quality control checks. Collaboration with data scientists and project managers is essential to clarify ambiguities and ensure that annotated data meets the project's requirements. Staying proactive in communication and continuous learning helps to minimize errors and improve overall data quality.

Does data annotation actually pay?

Data annotation research jobs typically pay hourly or per task rates, with wages ranging from minimum wage to higher rates depending on experience and complexity of the work. Many positions are freelance or remote, requiring basic skills in data labeling tools and attention to detail. Payment is generally reliable, but rates vary by employer and project.

How hard is it to get hired by data annotation?

Getting hired for a data annotation research role typically requires basic computer skills, attention to detail, and sometimes familiarity with annotation tools or platforms. Many positions are entry-level and do not require advanced education, making the hiring process relatively accessible for those with the right skills and reliability.

What is the difference between Data Annotation Research vs Data Labeling Specialist?

AspectData Annotation ResearchData Labeling Specialist
CredentialsTypically requires a background in data science, research methods, or related fieldsOften requires basic technical skills and experience with labeling tools
Work EnvironmentResearch labs, tech companies, or remote research teamsData centers, tech companies, or remote labeling teams
Industry UsageUsed in AI/ML research, developing annotation methodologiesUsed in preparing datasets for machine learning models
Search & Comparison IntentUnderstanding research-focused roles in data annotationLooking for practical data labeling jobs

Data Annotation Research involves exploring new annotation techniques and improving data quality for AI models, often requiring research skills. In contrast, Data Labeling Specialists focus on applying existing labeling tools to annotate datasets efficiently. Both roles are essential in AI development but differ in scope and expertise.

Is data annotation real or fake?

Data annotation is a real and essential process in machine learning and AI development, involving labeling data such as images, text, or audio to train algorithms. Data annotation jobs require attention to detail and often use tools like labeling platforms or software, making them a legitimate employment opportunity in the tech industry.

What is data annotation research?

Data annotation research involves studying and developing methods for labeling data, such as images, text, or audio, to be used in training machine learning models. Researchers in this field focus on improving annotation accuracy, efficiency, and scalability, as well as addressing challenges like bias and consistency. This work is critical because high-quality annotated data is essential for building effective AI systems. Data annotation research often includes exploring new tools, techniques, and guidelines for human annotators or automated labeling systems.

What are the key skills and qualifications needed to thrive as a Data Annotation Researcher, and why are they important?

To thrive as a Data Annotation Researcher, you need strong attention to detail, analytical thinking, and familiarity with data labeling concepts, often supported by a degree in computer science, linguistics, or a related field. Experience with annotation platforms, data management tools, and sometimes knowledge of programming languages like Python are typically required. Excellent communication, problem-solving abilities, and the capacity to work independently set standout contributors apart. These skills ensure high-quality, accurate data labeling, which is crucial for developing reliable AI and machine learning models.
What are popular job titles related to Data Annotation Research jobs in Boston, MA? For Data Annotation Research jobs in Boston, MA, the most frequently searched job titles are:
What job categories do people searching Data Annotation Research jobs in Boston, MA look for? The top searched job categories for Data Annotation Research jobs in Boston, MA are:
What cities near Boston, MA are hiring for Data Annotation Research jobs? Cities near Boston, MA with the most Data Annotation Research job openings:
Data Annotation Research jobs near you
Infographic showing various Data Annotation Research job openings in Boston, MA as of July 2026, with employment types broken down into 2% Locum Tenens, 33% Full Time, 26% Part Time, 2% Contract, 36% Nights, and 1% Summer. Highlights an 55% Physical, 2% Hybrid, and 43% Remote job distribution.

Senior Data Operations Engineer

FieldAI

Boston, MA

$110K - $140K/yr

Full-time

Posted 3 days ago

Job description

FieldAI is transforming how robots interact with the real world. Our growing R&D team is based in Boston, where we develop risk-aware, reliable, field-ready AI systems that tackle the hardest problems in robotics and unlock the potential of embodied intelligence. We take a pragmatic approach that goes beyond off-the-shelf, purely data-driven methods or transformer-only architectures, combining cutting-edge research with real-world deployment. Our solutions are already deployed globally, and we continuously improve model performance through rapid iteration driven by real field use.

About the Role
 

Field AI is transforming how robots interact with the real world. Our R&D team, the FieldAI Research Institute (FAIRI), is based in Cambridge, MA, where we build risk-aware, field-ready AI systems that unlock general purpose intelligence for robotics.

FAIRI is looking for a Senior Data Operations Engineer to run the day-to-day of our data operations function: building the tooling the pipeline runs on, staying hands-on enough to dogfood and stress-test that tooling yourself, and managing the interns and contractors who carry out the bulk of day-to-day collection and annotation. You’ll work directly with the Research Operations Partner to scale FAIRI’s in-house data function, and you’ll set the technical and operational bar the rest of the Data Operations Engineering team is built around.

What You’ll DoData Tooling & Infrastructure — 25%

  • Build and maintain hardware sensor suites — sensor harnesses, camera arrays, mounting fixtures, wearable sensor stacks (including soldering and cable assembly).

  • Write and maintain QA scripts for in-house and vendor data drops.

  • Build and maintain annotation software and other internal data tooling.

Data Collection & Annotation — 25%

  • Run motion capture, teleoperation, and human-subjects data collection sessions yourself — the fastest way to dogfood and stress-test tooling and protocols before handing them to the team.

  • Annotate robotics/AV datasets (object interaction, contact state, multi-agent) against FAIRI’s evaluation framework.

  • Use hands-on collection and annotation work to surface tooling gaps and drive the tooling roadmap above.

Team Management & Documentation — 25%

  • Manage and schedule data collection interns and contractors; own day-to-day throughput and quality.

  • Onboard and train interns/contractors on equipment, SOPs, and the informed-consent process.

  • Write and maintain SOPs and other supporting documentation for data collection, annotation, and lab operations.

  • Own first-level QC and escalation for intern/contractor output; flag protocol or safety issues.


Technical Demo Support — 25%

  • Learn the product stack and operate various robotic platforms to demonstrate FieldAI FFM (Field Foundation Model) capabilities.

  • Support demo planning and execution, coordinating with the Research Operations Partner

  • Help produce content showcasing FieldAI’s ability to deploy robots on dull, dirty,

and dangerous jobs.

  • Troubleshoot hardware and software issues live during demos with important stakeholders. 

What You Bring

You don’t need every skill below, but you should bring real, hands-on depth in several of them:

  • Soldering and cable assembly

  • Motion capture systems (e.g., Vicon, OptiTrack, markerless/IMU)

  • Data annotation for robotics or autonomous vehicles

  • QA for hardware and/or software

  • 3D scanning and 3D printing

  • Data collection and human subjects research (IRB/consent familiarity a plus)

  • AR/VR development or production

  • Python, Java, or equivalent scripting

  • LIDAR

  • Robotics (platforms, sensors, or control)

  • Linux command line

  • Blender or Unity

  • Film/TV production

 

Beyond the toolkit:

  • Comfortable moving between hardware and software in the same day: genuinely hands-on, not hands-off.

  • High ownership: you can take an open-ended ask (“troubleshoot why this data had issues ”) and run with it without much hand-holding.

  • Strong documentation habits: you leave SOPs and processes better than you found them.

What Sets You Apart

  • Background in film/TV production, game development, data operations, or another field where wearing every hat is normal

  • Interest in humanoid robotics and how machines learn from human movement

Why FAIRI

This role sits inside FAIRI’s Research Operations function, supporting the Humanoid Program. It’s built to grow: the Data Operations Engineering track is expected to scale from one person today to a small team over the next 12–18 months, and this hire is a leading candidate for Data Operations Engineering Lead as that team stands up.

Why Join Field AI?
FieldAI is tackling one of robotics’ hardest problems: deploying robots in unstructured, previously unknown environments. Our Field Foundational Models™ advance perception, planning, localization, and manipulation with an emphasis on explainability and safety, so our systems can be trusted where it matters most.

You will work alongside a world-class team that values creativity, resilience, and bold thinking. We bring a decade-long track record of real-world deployments, strong performance in DARPA challenges, and experience from organizations such as DeepMind, NASA JPL, Boston Dynamics, NVIDIA, Amazon, Tesla Autopilot, Cruise, Zoox, Toyota Research Institute, and SpaceX.

Our R&D organization is growing and anchored in Boston, with close collaboration across our teams in Southern California and with colleagues around the US and globally.

Be Part of the Next Robotics Revolution
Solving problems at this scale takes a team as unique as the mission. We are looking for people who push beyond conventional approaches, enjoy tackling tough and ambiguous questions, and bring interdisciplinary perspective. Our success depends on exceptional AI researchers and engineers, as well as strong software developers, product designers, field deployment experts, and communicators who can turn breakthroughs into real capability.
We are headquartered in Mission Viejo (Irvine adjacent), Southern California, with teammates across the US and around the world. Join us to shape the future of embodied intelligence as part of a fun, close-knit team building systems that work in the real world.

Equal Opportunity
FieldAI celebrates diversity and is committed to creating an inclusive environment for all employees. Candidates and employees are evaluated based on merit, qualifications, and performance. We do not discriminate on the basis of race, color, religion, sex, gender, national origin, ethnicity, veteran status, disability status, age, sexual orientation, gender identity, marital status, or any other legally protected status.

We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us.