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Data Annotation Engineer Jobs in Illinois (NOW HIRING)

Data Scientist II

Chicago, IL · On-site

$138 - $172/hr

Who We Want The Data Scientist II will work closely with Data Science, Product, and Engineering to ... Experience designing data annotation workflows, labeling guidelines, or label quality processes is ...

Data Scientist II

Chicago, IL · On-site +1

$130K - $150K/yr

Who We Want The Data Scientist II will work closely with Data Science, Product, and Engineering to ... Experience designing data annotation workflows, labeling guidelines, or label quality processes is ...

Who We Want The Data Scientist II will work closely with Data Science, Product, and Engineering to ... Experience designing data annotation workflows, labeling guidelines, or label quality processes is ...

... that AI developers have consent and access to high quality ingredients. TraceID puts everyone in ... Architect how we transform large-scale data systems (annotation, content detection, attribution ...

Data Annotation Engineer information

See Illinois salary details

$49.9K

$142.9K

$190.9K

How much do data annotation engineer jobs pay per year?

As of Aug 10, 2026, the average yearly pay for data annotation engineer in Illinois is $142,893.00, according to ZipRecruiter salary data. Most workers in this role earn between $81,400.00 and $189,900.00 per year, depending on experience, location, and employer.

What are the main challenges faced by data annotation engineers in their daily work?

One of the main challenges Data Annotation Engineers face is ensuring consistent accuracy and quality in labeling large and often complex datasets. Attention to detail is critical, as even small errors can significantly affect machine learning model performance. Additionally, engineers must frequently adapt to evolving annotation guidelines and emerging data types, which requires ongoing learning and flexibility. Collaboration with data scientists and project managers is common to clarify requirements and resolve ambiguities, making strong communication skills essential for success.

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

To thrive as a Data Annotation Engineer, you need a strong background in data analysis, attention to detail, and familiarity with annotation processes, often supported by a degree in computer science or a related field. Proficiency with annotation tools like Labelbox, CVAT, or VIA, and understanding of data formats used in machine learning, is commonly required. Excellent communication, collaboration, and organizational skills help you effectively manage projects and cooperate with cross-functional teams. These abilities are crucial for delivering high-quality labeled data, which directly impacts the performance of AI and machine learning models.

What is a data annotation engineer?

A Data Annotation Engineer is responsible for labeling and annotating data—such as text, images, audio, or video—to train machine learning models. They ensure that data is accurately categorized and structured to improve model performance. This role often involves using specialized annotation tools, following detailed guidelines, and working closely with data scientists and AI teams. Data Annotation Engineers play a crucial role in the development of AI applications by providing high-quality labeled datasets for supervised learning.

What are popular job titles related to Data Annotation Engineer jobs in Illinois? For Data Annotation Engineer jobs in Illinois, the most frequently searched job titles are:
What job categories do people searching Data Annotation Engineer jobs in Illinois look for? The top searched job categories for Data Annotation Engineer jobs in Illinois are:
What cities in Illinois are hiring for Data Annotation Engineer jobs? Cities in Illinois with the most Data Annotation Engineer job openings:
Infographic showing various Data Annotation Engineer job openings in Illinois as of August 2026, with employment types broken down into 54% Full Time, and 46% Contract. Highlights an 82% In-person, and 18% Remote job distribution, with an average salary of $142,893 per year, or $68.7 per hour.

Data Scientist II

Arrive Logistics

Chicago, IL • On-site

$138 - $172/hr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Re-posted 18 days ago


Arrive Logistics rating

5.5

Company rating: 5.5 out of 10

Based on 10 frontline employees who took The Breakroom Quiz


Job description

Who We Want

The Data Scientist II will work closely with Data Science, Product, and Engineering to build and improve ML and AI systems that drive operational value. This role is a great fit for a hands‑on practitioner with applied experience in NLP and LLM‑based systems who is ready to take on meaningful technical ownership. You’ll contribute to the full lifecycle of production ML systems — from evaluation and measurement through development, deployment, and iteration — with a particular focus on text and language‑based applications. The ideal candidate is comfortable operating in ambiguous problem spaces, can translate loosely defined business needs into concrete technical approaches, and communicates findings clearly to both technical and non‑technical audiences.

What You’ll Do
  • Develop, evaluate, and iterate on NLP and LLM‑based systems, including text classification, information extraction, and context retrieval pipelines.
  • Build measurement and evaluation frameworks — both offline and online — to assess where and why systems are underperforming and quantify the impact of improvements.
  • Develop golden test datasets and define methodologies for creating and maintaining them over time, including designing annotation guidelines and ensuring label quality.
  • Evaluate and apply the appropriate approach for language tasks — whether prompt engineering, fine‑tuning, or classical NLP methods — including modern retrieval and RAG architectures and LLM evaluation methodologies, based on the problem and available data.
  • Perform structured analysis of system performance to surface failure modes, data gaps, and high‑value areas for investment, applying sound statistical reasoning to evaluation results.
  • Partner with engineers to support deployment, integration, and monitoring of ML and AI systems in production.
  • Contribute to standards and best practices around deploying, evaluating, and monitoring text and language‑based ML systems.
  • Document work clearly and maintain knowledge artifacts that make systems understandable and maintainable over time.
  • Collaborate with senior data scientists and cross‑functional partners to translate business needs into well‑scoped technical solutions, including communicating findings and recommendations to non‑technical stakeholders.
Qualifications
  • Bachelor’s or Master’s degree in a quantitative field (computer science, statistics, linguistics, or related) and 2–4 years of applied ML or data science experience, or equivalent practical experience.
  • Hands‑on experience building or improving NLP or LLM‑based systems in applied settings.
  • Familiarity with text classification, information extraction, or other NLP tasks — and an understanding of where these systems fail.
  • Experience with both prompt engineering and fine‑tuning approaches for language tasks, with the judgment to know when to apply each.
  • Familiarity with modern retrieval strategies and RAG architectures and how they affect LLM system performance.
  • Experience with Hugging Face Transformers for text classification or related NLP tasks.
  • Experience contributing to evaluation frameworks, test sets, or performance diagnostics for ML systems, including comfort with statistical methods for measuring model performance.
  • Proficiency in Python and SQL, and comfort working with structured and unstructured data.
  • Ability to operate effectively in ambiguous problem spaces — scoping technical approaches when requirements are not fully defined.
  • Strong written communication skills; able to document systems and findings clearly and present recommendations to non‑technical stakeholders.
  • Experience designing data annotation workflows, labeling guidelines, or label quality processes is a plus.
  • Experience with model deployment, monitoring, or production ML workflows is a plus.
  • Familiarity with LangChain and LangSmith or similar LLM orchestration and observability tooling is a plus.
  • Transportation or logistics industry experience is a plus.
The Perks of Working With Us
  • Take advantage of our comprehensive benefits package, including medical, dental, vision, life, disability, and supplemental coverage.
  • Invest in your future with our matching 401(k) program.
  • Build relationships and take part in learning opportunities through our Employee Resource Groups.
  • Enjoy office wide engagement activities, team events, happy hours and more!
  • Leave the suit and tie at home; our dress code is casual.
  • Work in the heart of downtown Chicago, IL!
  • Sweat it out at the LifeStart gym in our office building that includes brand new Peloton bikes, top‑of‑the‑line equipment and personal training options.
  • Maximize your wellness with free counseling sessions through our Employee Assistance Program
  • Take time to manage your physical and mental health – we offer company paid holidays, paid vacation time and wellness days.
  • Receive 100% paid parental leave when you become a new parent.
  • Get paid to work with your friends through our Referral Program!
  • Get relocation assistance! If you are not local to the area, we offer relocation packages.

$138,000 – $172,000 a year

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