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Data Annotation Tech Jobs in Princeton, NJ (NOW HIRING)

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Product Content Engineer

New York, NY · On-site +1

$162K/yr

... frameworks, annotation guidelines, or quality rubrics for AI/ML systems * Demonstrated data ... Meta builds technologies that help people connect, find communities, and grow businesses. When ...

YO AI Labs

Medical Coder - Remote

New York, NY · Remote

$50 - $80/hr

Familiarity with digital annotation tools or healthcare data projects is a plus. * Commitment to accuracy, quality, and continuous learning in healthcare coding and technology

Forhyre

Prompt Engineers

New York, NY

We are a cutting-edge technology company at the forefront of the Artificial Intelligence (AI ... Solid knowledge of data collection, preprocessing, and annotation for prompt development.

Forhyre

Prompt Engineers

New York, NY

We are a cutting-edge technology company at the forefront of the Artificial Intelligence (AI ... Solid knowledge of data collection, preprocessing, and annotation for prompt development.

Meta

Product Manager, Evals & Improvement

New York, NY

$146K/yr

Partner with ML and data science to turn feedback into model improvements, eval frameworks, and ... Experience building annotation, labeling, or crowd-sourcing systems * Experience with reinforcement ...

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Data Annotation Tech information

See Princeton, NJ salary details

$12

$23

$36

How much do data annotation tech jobs pay per hour?

As of Aug 23, 2026, the average hourly pay for data annotation tech in Princeton, NJ is $23.95, according to ZipRecruiter salary data. Most workers in this role earn between $17.64 and $28.46 per hour, depending on experience, location, and employer.

What is a data annotation tech?

A Data Annotation Tech is responsible for labeling and categorizing data, such as text, images, audio, or video, to train machine learning models. They follow specific guidelines to ensure accuracy and consistency in annotations, which helps improve the performance of AI systems. This role often involves repetitive tasks, attention to detail, and familiarity with various annotation tools. Data annotation is crucial for AI development in industries like healthcare, finance, and autonomous driving.

What does a data annotation tech do?

A typical day as a Data Annotation Tech involves reviewing large sets of data—such as images, text, or audio—and accurately labeling or categorizing them using specialized software. You may work independently or as part of a team, following specific project guidelines to ensure data integrity and consistency. Collaboration with project managers or data scientists is common when clarifying ambiguous data points or addressing annotation challenges. Additionally, productivity targets and quality checks are a regular part of the workflow, helping to keep projects on schedule and maintain high standards.

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

To thrive as a Data Annotation Tech, you need keen attention to detail, basic computer literacy, and familiarity with data labeling standards, often supported by a high school diploma or equivalent. Experience with annotation platforms, image or text labeling tools, and basic knowledge of data management systems is highly valuable. Strong organizational skills, patience, and effective communication set top candidates apart in this field. These skills and qualities ensure annotated data is accurate, consistent, and valuable for machine learning or AI projects.

What are popular job titles related to Data Annotation Tech jobs in Princeton, NJ?

For Data Annotation Tech jobs in Princeton, NJ, the most frequently searched job titles are:

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The top searched job categories for Data Annotation Tech jobs in Princeton, NJ are:

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Cities near Princeton, NJ with the most Data Annotation Tech job openings:

Data Annotation Tech jobs near you
Infographic showing various Data Annotation Tech job openings in Princeton, NJ as of August 2026, with employment types broken down into 49% Full Time, and 51% Part Time. Highlights an 59% In-person, and 41% Remote job distribution, with an average salary of $49,806 per year, or $23.9 per hour.

Strategic Project Lead, Software Engineering

Turing

New York, NY • On-site

Full-time

Posted 5 days ago

Job description

About Turing
Based in San Francisco, California, Turing is the world's leading research accelerator for frontier AI labs and a trusted partner for global enterprises looking to deploy advanced AI systems. Turing accelerates frontier research with high-quality data, specialized talent, and training pipelines that advance thinking, reasoning, coding, multimodality, and STEM. For enterprises, Turing builds proprietary intelligence systems that integrate AI into mission-critical workflows, unlock transformative outcomes, and drive lasting competitive advantage.
Recognized by Forbes, The Information, and Fast Company among the world's top innovators, Turing's leadership team includes AI technologists from Meta, Google, Microsoft, Apple, Amazon, McKinsey, Bain, Stanford, Caltech, and MIT. Learn more at www.turing.com
The Role
You will own the production system behind Turing's software-engineering data programs, turning complex research requirements into predictable delivery across quality, throughput, contributor performance, timelines, and cost.
These programs may involve supervised coding demonstrations, repository-level tasks, agentic trajectories, reinforcement-learning environments, benchmarks, code review, and rubric-based evaluations. They can require coordinating hundreds of distributed software engineers while responding quickly to changing research requirements.
This is an operations leadership role with a meaningful technical bar. You must be able to inspect code, understand tests, interrogate quality signals, and challenge a workflow or rubric when it is not producing the intended result. You will not be expected to act as the principal engineer for every program. Your primary responsibility is to build and operate the system that consistently produces high-quality technical work at scale.
What You'll Do
1) Operational execution - own end-to-end delivery on every project you run
  • Design and manage data pipelines from customer specification to final delivery, with full accountability for scope, timeline, and quality.
  • Diagnose bottlenecks in real time - re-sequence workflows, refine instructions, create incentive systems, and scale review processes to hit throughput targets.
  • Run daily "war room" syncs to stay ahead of issues before they reach the customer.

2) Customer relationships - be the face of Turing to the world's leading AI labs
  • Act as the primary point of contact for researchers and program managers at frontier AI labs.
  • Deliver clear, consistent reporting and proactively anticipate client needs before they ask.
  • Build the kind of long-term trust that converts a one-off project into a multi-year partnership - and identify expansion opportunities along the way.

3) Large-scale coordination - orchestrate the work of 100-1,000+ contributors
  • Source, vet, onboard, train, and performance-manage domain experts across distributed workspaces.
  • Maintain high execution standards at every stage of production, from annotation through review through delivery.
  • Design motivation and performance systems - including gamification - that keep large contributor pools engaged and output high.

4) Quality ownership - ensure world-class data integrity on every project
  • Own quality control across the annotation lifecycle: set the bar, measure against it, and close the gap when it slips.
  • Analyze datasets to identify trends, anomalies, and systematic errors - then fix the root cause, not just the symptom.
  • Implement and continuously improve annotation, evaluation, and curation best practices.

5) Process innovation - make the operation faster, better, and cheaper each cycle
  • Stay ahead of emerging practices in AI data operations and apply them before customers ask.
  • Champion workflow changes that reduce task completion times and improve cost efficiency.
  • Maintain clear, scalable documentation so that improvements survive beyond any single project.

6) Playbook building - codify what works so future SPLs scale faster than you did
  • Document onboarding scripts, quality benchmarks, contributor management frameworks, and escalation patterns.
  • Own your domain's section of the SPL knowledge base.
  • Actively mentor the next hire - your playbook is your legacy.
Who We're Looking For
  • Background in consulting, finance, startups, or other operationally intense environments, with a proven track record of managing complex, multi-stakeholder projects.
  • Strong analytical and communication abilities: you can spot a bottleneck in a noisy production environment, build a measurement plan, and communicate the fix to a demanding client in plain language.
  • Customer-facing experience: comfortable working directly with high-profile clients, managing expectations, and building long-term relationships.
  • Excited by gritty process optimization and large-scale execution - you thrive on making complex operations faster, cleaner, and more reliable.
What Success Looks Like
30 days: First project delivered end-to-end with no quality escapes reaching the customer. Reporting cadence established and trusted by the lab. Contributor onboarding playbook v1 published. You know the names of every researcher on your accounts.
60 days: 300+ active contributors across concurrent workstreams, all executing to standard. At least one customer has proactively expanded scope based on delivery quality. Quality framework codified and in daily use by your team.
180 days: $5M+ in active project revenue under your management. A second SPL is ramping off your playbook. You spend more time multiplying through others than operating as a solo contributor.
Why Turing
  • Work directly with the world's leading AI labs at the cutting edge of post-training, evaluation, and agentic AI research.
  • Real impact on the path to AGI: the data you deliver will directly influence how frontier models are trained and evaluated.
  • High ownership and influence. You will shape how Turing delivers at scale, with direct visibility to senior leadership.
  • Direct-to-research customers. You will spend your time partnering with the people building the future of AI, not coordinating with procurement.
How to Apply
Send a CV and a short note on a project you managed end-to-end - ideally something that required coordinating a large team, managing a demanding client, or solving a hard quality problem under time pressure - to recruiting@turing.com. We read every submission.
Compensation
SPL:
  • Base Salary: $120K-$200K
  • Total Target Compensation: $195K-$300K (includes salary, variable, and equity)

Senior SPL:
  • Base Salary: $150K-$280K
  • Total Target Compensation: $300K-$500K (includes salary, variable, and equity)

Values
  • We are client first: We put our clients at the center of everything we do, because their success is the ultimate measure of our value.
  • We work at Start-Up Speed: We move fast, stay agile and favor action because momentum is the foundation of perfection
  • We are AI forward: We help our clients build the future of Al and implement it in our own roles and workflow to amplify productivity.
Advantages of joining Turing
  • Amazing work culture (Super collaborative & supportive work environment; 5 days a week)
  • Awesome colleagues (Surround yourself with top talent from Meta, Google, LinkedIn etc. as well as people with deep startup experience)
  • Competitive compensation

Don't meet every single requirement? Turing is proud to be an equal opportunity employer. We do not discriminate on the basis of race, religion, color, national origin, gender, gender identity, sexual orientation, age, marital status, disability, protected veteran status, or any other legally protected characteristics. At Turing we are dedicated to building a diverse, inclusive and authentic workplace and celebrate authenticity, so if you're excited about this role but your past experience doesn't align perfectly with every qualification in the job description, we encourage you to apply anyways. You may be just the right candidate for this or other roles.
For applicants from the European Union, please review Turing's GDPR notice here.

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