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Technical Data Annotation Analyst Jobs in Chicago, IL

Overview Welo Data is hiring Croatian-speaking analysts to support our Speech & Voice AI team. You ... Strong written communication and language fundamentals * 1+ year in labeling/annotation/content ...

Data & Analytics Engineer

Chicago, IL ยท On-site +1

$118K - $141K/yr

Role Overview The Full Stack Data & Analytics Engineer is Collectiv's most versatile technical consultant, combining deep data engineering expertise with advanced Power BI and analytics delivery ...

Data & Analytics Engineer

Chicago, IL ยท On-site +1

$118K - $141K/yr

Role Overview The Data & Analytics Engineer is Collectiv's most versatile technical consultant, combining deep data engineering expertise with advanced Power BI and analytics delivery capabilities.

We are currently seeking a talented Lead Data Analyst to join us as we develop our data-driven ... Strong technical aptitude and ability to learn new technical products and skills quickly * Strong ...

Data Analyst

Chicago, IL ยท Hybrid

$75K - $95K/yr

They will make data and analysis accessible to non-technical audiences. The role works extensively within the Microsoft Azure and Microsoft Fabric ecosystems and involves close collaboration with ...

We are currently seeking a talented Lead Data Analyst to join us as we develop our data-driven ... Strong technical aptitude and ability to learn new technical products and skills quickly * Strong ...

We are currently seeking a talented Lead Data Analyst to join us as we develop our data-driven ... Strong technical aptitude and ability to learn new technical products and skills quickly * Strong ...

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Analyze data from multiple enterprise applications and identify relationships, dependencies, and ... Ability to turn business requirements into clearly defined technical data solutions. * Knowledge of ...

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Technical Data Annotation Analyst information

See Chicago, IL salary details

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$53

$75

How much do technical data annotation analyst jobs pay per hour?

As of Sep 9, 2026, the average hourly pay for technical data annotation analyst in Chicago, IL is $53.67, according to ZipRecruiter salary data. Most workers in this role earn between $47.31 and $60.67 per hour, depending on experience, location, and employer.

What is the difference between Technical Data Annotation Analyst vs Data Labeling Specialist?

AspectTechnical Data Annotation AnalystData Labeling Specialist
Required CredentialsHigh school diploma or equivalent; familiarity with data annotation toolsHigh school diploma or equivalent; experience with labeling platforms
Work EnvironmentOffice or remote; collaborative with data science teamsRemote or on-site; focused on labeling tasks
Industry UsageTech, AI, autonomous vehicles, healthcareAI, machine learning, computer vision projects

The Technical Data Annotation Analyst and Data Labeling Specialist roles share similar credentials and work environments, often overlapping in AI and machine learning industries. However, the analyst typically involves more technical understanding and collaboration with data teams, while the specialist focuses primarily on labeling tasks. Both roles are essential in preparing data for AI models, but the analyst may require additional technical skills or familiarity with annotation tools.

What does a technical data annotation analyst do?

A technical data annotation analyst labels and categorizes data such as images, videos, or text to help train machine learning models. They use specialized tools and follow guidelines to ensure data accuracy and consistency, often working with large datasets in a structured environment.

Machine Learning PhD Student, Frontier AI Evaluation (Contract)

Mundelein, IL โ€ข On-site

Other

Posted 9 days ago


Job description

About the role:

Cobalt is seeking current PhD students working in machine learning to produce the expert reasoning and evaluation data used to train and assess frontier AI models.

This opportunity is suited to students who are actively doing ML research: designing and running experiments, training and evaluating models, working through derivations, and debugging results that do not behave as expected. You may be at any stage of your program, from first year through writing up, and you do not need to have published yet.

You do not need prior experience in data annotation or model evaluation. What matters is that you can solve non-trivial ML problems unaided and explain your reasoning clearly in writing.


What you'll do:

Depending on the project, you may:

  • Produce written reasoning traces on hard ML problems, capturing how you reach a solution rather than only the solution itself, and draft expert reference answers to technical questions
  • Author novel problems in your subfield that have verifiable or defensible correct answers
  • Evaluate model-generated technical content: compare and rank responses, articulate what makes the stronger one stronger, and identify the specific step at which a chain of reasoning breaks down
  • Assess whether stated conclusions are supported by the underlying derivation, code, or experimental evidence
  • Design rubrics and partial-credit criteria for scoring multistep technical tasks

Projects follow their own guidelines, formatting conventions, and quality standards, and you will work with feedback from reviewers and lab research teams.


Required qualifications:

  • Current enrollment in a PhD program in machine learning, computer science, statistics, mathematics, physics, or a closely related quantitative discipline, with research that is substantially ML focused, at any stage
  • Demonstrated depth in at least one area, for example optimization, reinforcement learning, language model training and post-training, learning theory, probabilistic methods, computer vision, natural language processing, or systems for ML
  • Ability to solve advanced ML problems independently, to interpret papers, derivations, code and experimental results, and to explain each step of your reasoning clearly in writing
  • Strong attention to detail, a commitment to factual accuracy, and the ability to work independently to agreed timelines
  • Confirmation that outside contract work is permitted under your visa status, funding terms, and institutional policies. Applicants are responsible for verifying this, and we cannot advise on it.

Publications at venues such as NeurIPS, ICML, ICLR, ACL, or CVPR are useful but not required, as is teaching assistant, grading, or peer review experience.


Why join Cobalt AI:

  • Advance frontier AI where it counts. Apply your expertise to data that frontier labs cannot obtain any other way, where your reasoning directly shapes how the next generation of models works through technical problems.
  • Grow professionally. Expand your influence through evaluation projects, advisory roles, and research collaborations, while developing a working understanding of how frontier models are trained and assessed.
  • Work with a top-tier network. Collaborate with researchers and engineers from leading institutions and labs on high-impact, flexible work.
  • Set your own schedule. Flexible 10 to 40 hour weeks that fit around your existing work and your life.
  • Competitive pay. Rates vary by project and are determined by a number of factors, including scope, skillset, and experience.