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Data Annotation Engineer Jobs (NOW HIRING)

Abaka AI

Data Operations Engineer

Mountain View, CA · On-site

$136.30K - $163.60K/yr

The Data Operations Engineer will manage the internal dataset library and collaborate with various ... with data annotation, labeling workflows, or dataset preparation for machine learning. • ...

Nuro

Software Engineer, ML Data Infrastructure

Mountain View, CA · On-site

$136.30K - $163.60K/yr

... data annotation tools to support first-party and third-party labeling workforce to provide high ... Engineering, or a closely related field Preferred : • Strong proficiency in C++ or other high ...

Figure

Helix AI Engineer, Tooling

San Jose, CA · Hybrid

$150K - $250K/yr

Design and build intuitive web interfaces for robot data annotation, datasets visualization, and ... Strong software engineering fundamentals * Bachelor's or Master's degree in Computer Science ...

Encord

Human Data Solutions Engineer

San Francisco, CA · On-site

$134.90K - $162K/yr

The role As a Human Data Operations & Solutions Engineer at Encord, you will sit at the ... You'll own the full arc: leading technical discovery on demo calls, designing the annotation ...

Applied Intuition

Data Quality Specialist

Sunnyvale, CA · On-site

... annotation and labeling to support machine learning model training • Document quality standards and create comprehensive reports on data quality metrics • Collaborate with engineering teams to ...

Comrise

CA · On-site

$26 - $29/wk

Programming: Program parts using 2D and/or 3D toolpaths with Surfcam or Mastercam on mills and lathes. * Blueprint Reading: Read and interpret prints, specification sheets, and 3D files to determine ...

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Data Annotation Engineer information

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$51.5K

$147.5K

$197K

How much do data annotation engineer jobs pay per year?

As of May 30, 2026, the average yearly pay for data annotation engineer in the United States is $147,461.00, according to ZipRecruiter salary data. Most workers in this role earn between $84,000.00 and $196,000.00 per year, depending on experience, location, and employer.

What is a Data Annotation Engineer job?

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 the key skills and qualifications needed to thrive in the Data Annotation Engineer position, and why are they important?

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 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.
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Data Annotation Engineer jobs near you
Infographic showing various Data Annotation Engineer job openings in the United States as of May 2026, with employment types broken down into 33% As Needed, and 67% Part Time. Highlights an 4% Physical, and 96% Remote job distribution, with an average salary of $147,461 per year, or $70.9 per hour.
Annotation Data Scientist, Evaluation Integrity (Siri)

Annotation Data Scientist, Evaluation Integrity (Siri)

Apple

Cambridge, MA • On-site

Full-time

Posted 11 days ago

Apple rating

8.1

Company rating: 8.1 out of 10

Based on 661 frontline employees who took The Breakroom Quiz

6th of 30 rated technology retailers

Job description

Play a part in the ongoing revolution in human-computer interaction. Siri is evolving - and the way we evaluate it has to evolve with it. Join the Evaluation Integrity team to help build the trusted quality signal behind every Siri release..Within the Siri evaluation organization, the Human Evaluation sub-team is responsible for answering the question: can we trust our evals? We do that by designing human-in-the-loop (HITL) annotation tasks that scrutinize every moving part of an agentic evaluation - the simulated user agent, the conversation it has with Siri, and the automated evaluators that grade the exchange. This role sits at the intersection of data science, human annotation engineering, and evaluation methodology, and is instrumental in turning human judgment into a rigorous, reproducible signal that directly informs pre-ship model and product decisions..
As an Annotation Data Scientist on the Evaluation Integrity team, you will design and run HITL annotation projects that evaluate the quality and authenticity of agentic user personae, the validity of agent-to-agent conversations, and the reliability of LLM-as-judge and rule-based evaluators against Siri's product specifications. You will own annotation initiatives end-to-end; from rubric design and tooling, through annotator calibration, to data science analysis that turns annotator judgments into actionable signal for modeling, planning, and product teams.
Bachelor's or Master's degree in a quantitative or related field such as Data Science, Computer Science, Linguistics, Statistics, or Cognitive Science, or equivalent job-related experience.5+ years of hands-on experience working with human-annotated datasets or human-in-the-loop evaluation methodologies for machine learning, natural language processing, or large language model systems.5+ years of experience using Python for data processing, analysis, and prototyping, including experience with libraries such as pandas, Jupyter, and at least one data visualization library.Experience designing, implementing, and communicating annotation schemas, rubrics, or ontologies for machine learning training or evaluation data.Experience managing multiple concurrent dataset curation efforts, including scoping work, iterating on guidelines, coordinating with in-house or vendor annotators, and monitoring annotator performance metrics such as accuracy, throughput, and inter-annotator agreement.Experience specifying or designing custom annotation tooling in collaboration with software engineers.
Experience evaluating LLM-powered or agentic systems, including familiarity with LLM-as-judge methodologies, rubric-based grading, or trajectory and tool-call evaluation.Familiarity with statistical methods that address accuracy and variability in human annotation data, such as inter-annotator agreement, Cohen's or Fleiss' kappa, Krippendorff's alpha, or bootstrapping.Data-querying experience with SQL, Spark, or similar, and comfort working with large, complex, real-world datasets.Experience building pre-ship evaluation pipelines for conversational or assistant products.Experience with prompt engineering, or with designing simulated user personae for agent evaluation.Experience running annotation programs across multiple locales or at large scale.Excellent written and verbal communication skills, with the ability to explain technical topics clearly to data scientists, engineers, annotators, and cross-functional partners.Proven ability to collaborate effectively across functions and drive projects of varying sizes and scopes - knowing when to dive deep and when to delegate.

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Hours and flexibility

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About Apple

Sourced by ZipRecruiter

Imagine what you could do here! At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Dynamic, intelligent people and inspiring, innovative technologies are the norm here. The people who work here have reinvented entire industries with all Apple Hardware products. The same real passion for innovation that goes into our products also applies to our practices strengthening our dedication to leave the world better than we found it.

Industry

Computer and electronic product manufacturing

Company size

10,000+ Employees

Headquarters location

Cupertino, CA, US

Year founded

1976

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