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Data Annotation Software Engineer Jobs (NOW HIRING)

Data Annotation Technician Join Q Analysts and become part of a world-class organization. Q ... devices, software apps and experiences as well as Ground Truth Data Services for artificial ...

... devices, software apps and experiences as well as Ground Truth Data Services for artificial ... Q Analysts is looking for Data Annotation Technicians to support Ground Truth Data Collection ...

$120K - $155K/yr

Required Qualifications * 3+ years of experience in software engineering, data tooling, ML data operations, annotation systems, data QA, or related technical work. * Strong Python skills, including ...

... devices, software apps and experiences as well as Ground Truth Data Services for artificial ... Q Analysts is looking for Data Annotation Technicians to support Ground Truth Data Collection ...

Build and maintain annotation software and other internal data tooling. Data Collection ... It's built to grow: the Data Operations Engineering track is expected to scale from one person ...

Showing results 21-40

Data Annotation Software Engineer information

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$44.5K

$129.7K

$177.5K

How much do data annotation software engineer jobs pay per year?

As of Sep 10, 2026, the average yearly pay for data annotation software engineer in the United States is $129,716.00, according to ZipRecruiter salary data. Most workers in this role earn between $114,500.00 and $137,500.00 per year, depending on experience, location, and employer.

What is a data annotation software engineer?

Data Annotation Software Engineers are professionals who design, develop, and maintain software tools and systems that enable the labeling or tagging of data for use in machine learning and artificial intelligence projects. They help automate and streamline the data annotation process, ensuring that large volumes of data—such as images, audio, or text—are accurately labeled for model training. Their work often involves developing user interfaces, integrating annotation tools with data pipelines, and optimizing workflows to improve efficiency and data quality. These engineers play a critical role in ensuring that AI models are trained on high-quality, well-labeled datasets.

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

To thrive as a Data Annotation Software Engineer, you need strong programming skills (typically in Python or Java), experience with machine learning workflows, and a degree in computer science or a related field. Familiarity with annotation tools (like Labelbox or Supervisely), data labeling platforms, and version control systems such as Git is commonly required. Attention to detail, problem-solving abilities, and effective communication are valuable soft skills in this position. These skills ensure the creation of high-quality annotated datasets, which are crucial for training accurate machine learning models.

What are the main challenges data annotation software engineers face when ensuring data quality for machine learning projects?

Data Annotation Software Engineers often encounter challenges related to maintaining high-quality, consistent labels across large and diverse datasets. Ambiguous data, evolving project requirements, and aligning annotation guidelines with real-world scenarios can make this work complex. Engineers need to develop robust tools, implement quality checks, and collaborate closely with data scientists and annotation teams to ensure that the labeled data meets project standards. Continuous feedback loops and automation can help address these issues, but attention to detail and adaptability are essential for success in this role.

What is the difference between Data Annotation Software Engineer vs Data Scientist?

AspectData Annotation Software EngineerData Scientist
Required CredentialsBachelor's in CS, Data Science, or related; experience with annotation toolsBachelor's or higher in CS, Statistics, or related; advanced analytics skills
Work EnvironmentCollaborates with ML teams, focuses on annotation tools and pipelinesAnalyzes data, builds models, interprets results
Industry UsageUsed in AI/ML development, data labeling projectsApplied in predictive modeling, data analysis, research

While both roles work within data and AI projects, Data Annotation Software Engineers primarily develop and maintain annotation tools and pipelines, focusing on data labeling processes. Data Scientists analyze and interpret data to build models. The roles often collaborate but differ in technical focus and responsibilities.

Does data annotation really pay well?

Data annotation software engineers typically earn competitive salaries that vary based on experience, location, and skill level. Entry-level roles may pay modestly, while experienced professionals with expertise in annotation tools and machine learning can command higher wages. Overall, the role offers decent pay compared to many entry-level tech positions.

What are popular job titles related to Data Annotation Software Engineer jobs?

For Data Annotation Software Engineer jobs, the most frequently searched job titles are:

Infographic showing various Data Annotation Software Engineer job openings in the United States as of September 2026, with employment types broken down into 1% Internship, 1% As Needed, 83% Full Time, 12% Part Time, and 3% Contract. Highlights an 85% Physical, 3% Hybrid, and 12% Remote job distribution, with an average salary of $129,716 per year, or $62.4 per hour.

Software Engineer II - Fleet Enablement & Insights (Annotation Platform)

Fort Worth, TX • On-site

Socket.dev
Network Security • 1 - 10 employees

$93K - $127K/yr

Other

Medical, Dental, Vision, Life, Retirement, PTO

Posted 19 days ago


Job description

About the Company

At Torc, we have always believed that autonomous vehicle technology will transform how we travel, move freight, and do business. A leader in autonomous driving since 2007, Torc has spent over a decade commercializing our solutions with experienced partners. Now a part of the Daimler family , we are focused solely on developing software for automated trucks to transform how the world moves freight. Join us and catapult your career with the company that helped pioneer autonomous technology, and the first AV software company with the vision to partner directly with a truck manufacturer.

Meet the Team

The Software Engineer II will be a core member of the Fleet Enablement & Insights team, building Torc's in-house annotation platform: the web-based tooling that turns multi-sensor autonomy data into the labeled datasets that train and validate the autonomous truck platform. This role develops the interactive 2D/3D annotation editor and the services behind it which fuses HD map data and multi-camera, lidar, and other sensor context into the labeling workflow. The platform also serves adjacent use cases across the data organization, including data QC and scene-selection review. The ideal candidate is a collaborative engineer who thrives in a fast-paced environment and is passionate about high-performance visualization of large sensor datasets, thoughtful annotator-facing UX, and the pipelines that connect human review to machine learning at scale. This position offers the opportunity to work at the intersection of software engineering, computer graphics, and machine learning with a direct line of sight to the data that trains and validates the AV stack.

What You’ll Do
  • Design, develop, and maintain the TypeScript/React web application for 2D and 3D annotation, including cuboid and polygon editing, cross-frame interpolation and track propagation, attribute editing, and review-first (accept/reject) workflows.
  • Build high-performance point cloud and image rendering with three.js/WebGL: octree/LOD-based streaming formats, predictive prefetching for smooth frame scrubbing, camera-LiDAR projection, and multi-sensor overlays across a high camera count.
  • Design and build the services behind the editor: label storage and versioning, task assignment and QA workflow, authentication, and multi-user isolation guardrails.
  • Integrate pre-labeling and pseudo-labeling pipeline outputs into the annotation workflow, and instrument acceptance-rate and throughput metrics that drive the auto-labeling feedback loop.
  • Fuse HD map data into annotation and QC workflows as priors and reference layers for labeling and validation.
  • Build data converters and ingestion paths from Torc's multi-sensor scene data (multiple LiDARs, many cameras, calibration data) into the platform's formats.
  • Deliver dataset exports compatible with downstream ML training and validation consumers, with the lineage and auditability the safety case requires.
  • Leverage AWS cloud services and Databricks adjacency to host scene data and deploy scalable, reliable services.
  • Collaborate closely with the Data Annotation team (the platform's primary users), Autonomy/ML, Scene Selection, Mapping, and Data Engineering to align the tool with real annotator workflows and downstream requirements.
  • Participate in agile ceremonies, sprint planning, and weekly demos with annotators and stakeholders to keep the tool grounded in real use.
  • Contribute to a culture of engineering excellence through code reviews, documentation, and knowledge sharing, including hardening prototype code into production systems.
  • Identify and address technical debt, performance bottlenecks, and reliability gaps across the annotation platform.
What You’ll Need to Succeed
  • Strong proficiency in TypeScript and React, with experience building and shipping production-quality web applications.
  • Experience with browser-based 3D graphics (three.js, WebGL, or similar), or strong graphics fundamentals and a demonstrated ability to ramp quickly.
  • Proficiency in Python for building production backend services and APIs.
  • Experience working with large binary or sensor datasets (point clouds, imagery, video) and optimizing data-heavy user interfaces for performance.
  • Strong proficiency with SQL and hands‑on experience with PostgreSQL for label, task, and metadata storage.
  • Experience with AWS services for hosting data and deploying services.
  • Proficiency with Git and GitHub for version control, branching strategies, and collaborative code workflows.
  • Familiarity with JIRA or similar project management tools for tracking tasks, bugs, and sprint deliverables.
  • Solid understanding of software engineering fundamentals including data structures, algorithms, and system design.
  • Strong written and verbal communication skills with the ability to effectively collaborate across technical and non-technical stakeholders, including non-engineer users of the tools you build.
  • Bachelor's degree in Computer Science, Software Engineering, or a related technical field or equivalent experience.
Bonus Points
  • Experience with point cloud rendering and streaming formats (octree/LOD structures such as Potree or COPC, 3D Tiles, LAS/LAZ) or large-scale spatial data structures.
  • Experience building or extending annotation/labeling tools.
  • Familiarity with robotics data and visualization ecosystems (e.g., Rerun, Foxglove, MCAP, ROS bags).
  • Background in machine learning workflows for perception: object detection, tracking, segmentation, model-assisted or auto‑labeling, active learning.
  • Understanding of multi‑view geometry and sensor calibration (camera intrinsics/extrinsics, LiDAR‑camera projection, time synchronization).
  • Prior experience working with High‑Definition (HD) maps, map formats (e.g., OpenDRIVE, NDS, Lanelet2), or fusing map data into perception or labeling workflows.
  • Familiarity with PostGIS or spatial queries for geometry operations and geospatial data management.
  • Experience with Databricks or similar platforms for large-scale data processing.
  • Contributions to open‑source graphics, geospatial, annotation, or data engineering projects.
Perks of Being a Full-time Torc’r
  • A competitive compensation package that includes a bonus component and stock options
  • 100% paid medical, dental, and vision premiums for full‑time employees
  • 401K plan with a 6% employer match
  • Flexibility in schedule and generous paid vacation (available immediately after start date)
  • AD+D and Life Insurance

At Torc, we’re committed to building a diverse and inclusive workplace.

We celebrate the uniqueness of our Torc’rs and do not discriminate based on race, religion, color, national origin, gender (including pregnancy, childbirth, or related medical conditions), sexual orientation, gender identity, gender expression, age, veteran status, or disabilities.

Even if you don’t meet 100% of the qualifications listed for this opportunity, we encourage you to apply.

Our compensation reflects the cost of labor across several geographic markets. Pay is based on a number of factors and may vary depending on job-related knowledge, skills, and experience. Torc's total compensation package will also include our corporate bonus and stock option plan. Dependent on the position offered, sign‑on payments, relocation, and other forms of compensation may be provided as part of a total compensation package, in addition to a full range of medical, financial, and/or other benefits.

Job ID: 102797 Hiring Range for Job Opening US Pay Range $139,000 — $166,800 USD

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