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Day Data Annotation Jobs in New York (NOW HIRING)

triomics inc.

Forward Deployed ML Engineer

Manhattan, NY · On-site

$90 - $130/hr

... Days Days 1-30: Learn the stack, the data, and the domain. You should be reading real patient ... annotation team, run precision/recall per variable, and iterate until accuracy targets are met. You ...

Triomics

Forward Deployed ML Engineer

New York, NY · On-site

$170K - $190K/yr

... Days Days 1-30: Learn the stack, the data, and the domain. You should be reading real patient ... annotation team, run precision/recall per variable, and iterate until accuracy targets are met. You ...

New

Mecka AI

Strategic Project Lead, Sciences

New York, NY · On-site

$150K - $200K/yr

Serve as the day-to-day owner for your customer program - timelines, risks, deliverables, quality ... Build quality checks that catch scientific, procedural, and annotation errors before data reaches ...

Mecka

Strategic Project Lead, Sciences

Manhattan, NY · On-site

$90 - $120/hr

Serve as the day-to-day owner for your customer program -- timelines, risks, deliverables, quality ... Build quality checks that catch scientific, procedural, and annotation errors before data reaches ...

Mercor

Engineering Manager, Applied AI

New York, NY · On-site

$250K - $400K/yr

We're a leading AI data company, building the layer between human expertise and frontier models ... Millions of domain experts on the platform are paid over $4 million per day to train frontier AI ...

Omnicom

Scientific Associate

New York, NY · Hybrid

... annotation. In each project, you will have the opportunity to monitor and manage budget and ... We will process your personal data in accordance with our Recruitment Privacy Notice. Link to ...

Omnicom

Scientific Associate

New York, NY · On-site

... annotation. In each project, you will have the opportunity to monitor and manage budget and ... We will process your personal data in accordance with our Recruitment Privacy Notice. Link to ...

Mercor

Software Engineer, Agents

New York, NY · On-site

$130K - $500K/yr

Studio - We own Mercor's evaluation system & annotation platform for RL environments and tasks. We ... company data rooms that support tasks spanning hours to days. * Build tooling that turns agent ...

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All JobsDay Data Annotation JobsDay Data Annotation Jobs in New York

Day Data Annotation information

What is a day data annotation job?

Day Data Annotation jobs involve reviewing and tagging data, such as images, text, audio, or video, during regular daytime hours. Annotators help prepare datasets for machine learning and artificial intelligence by labeling or categorizing information according to specific guidelines. This work is essential for training algorithms to recognize patterns, objects, or language. Day Data Annotation can be done remotely or in-office, and it often requires attention to detail and good communication skills.

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

To excel as a Day Data Annotation Specialist, you need strong attention to detail, data entry accuracy, and a solid understanding of the subject matter being annotated, often supported by a high school diploma or relevant experience. Familiarity with annotation tools, spreadsheets, and data management software is typically required. Excellent concentration, time management, and clear communication skills help professionals stand out in this role. These abilities are crucial to ensure high-quality, consistent data labeling that directly impacts the performance of machine learning models and downstream business applications.

What are some common challenges faced by day data annotation specialists and how can they be addressed?

Day Data Annotation specialists often encounter challenges such as maintaining high accuracy while handling repetitive tasks, interpreting ambiguous data, and meeting tight deadlines. To address these, it's important to develop strong attention to detail, use project guidelines as references, and communicate with team leads or peers when uncertainties arise. Many organizations also provide regular feedback and quality assurance checks, which help annotators improve their performance and consistency over time.

What is the difference between Day Data Annotation vs Data Labeler?

AspectDay Data AnnotationData Labeler
CredentialsBasic computer skills, attention to detailBasic computer skills, attention to detail
Work EnvironmentRemote or on-site, collaborative teamsRemote or on-site, independent work
Industry UsageAI/ML companies, tech firmsAI/ML, data processing companies
Job FocusAnnotating data for machine learning modelsLabeling data to train AI systems

Day Data Annotation and Data Labeler roles are similar, focusing on preparing data for AI. Day Data Annotation often involves more detailed annotation tasks, while Data Labelers may perform broader labeling activities. Both roles require basic technical skills and are vital in AI development across tech industries.

Can I do data annotation with no experience?

Day data annotation jobs often do not require prior experience, as training is typically provided to teach you how to label data accurately. Basic computer skills and attention to detail are usually sufficient to start, and some roles may require familiarity with annotation tools or platforms. Entry-level positions are common and can serve as a stepping stone to more advanced data-related roles.

What are the most commonly searched types of Data Annotation jobs in New York?

The most popular types of Data Annotation jobs in New York are:

What cities in New York are hiring for Day Data Annotation jobs?

Cities in New York with the most Day Data Annotation job openings:

Day Data Annotation jobs near you

Strategic Project Lead, Software Engineering

Turing

New York, NY • On-site

Full-time

Posted 4 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
  • Flexible working hours

Don't meet every single requirement? Studies have shown that women and people of color are less likely to apply to jobs unless they meet every single qualification. 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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