Software Engineer II – Blacksburg, VA
The Software Engineer II at Confidential Client will develop and maintain a sophisticated web-based annotation platform critical for labeling multi-sensor data used to train autonomous truck systems. This role involves building high-performance 2D/3D visualization tools, backend services, and integrating machine learning workflows, collaborating closely with cross-functional teams to enhance data quality and annotation efficiency in a fast-paced environment.
About Careertakes
👉 Important disclosure: Careertakes is a third-party recruiting platform supporting this hiring process. If selected, you will be employed directly by our client, Software Development.
Applicants for this role may also receive access to additional matched opportunities through the Careertakes platform.
What You’ll Do
The Engineering team for the annotation platform builds the web-based tooling that turns multi-sensor autonomy data into labeled datasets used to train and validate autonomous systems. As a Software Engineer II on the Fleet Enablement & Insights (Annotation Platform) team, you will design, build, and maintain both the interactive 2D/3D annotation editor and the services that power it. You will work across front-end visualization, backend services, and data ingestion pipelines to deliver reliable, high-performance tools used by annotators and ML workflows.
- Design, develop, and maintain a TypeScript + React web application for 2D/3D annotation (cuboids, polygons, interpolation, track propagation, attribute editing, and review workflows).
- Implement high-performance point cloud and image rendering using three.js/WebGL: octree/LOD streaming, predictive prefetching, camera–LiDAR projection, and synchronized multi-sensor overlays.
- Build backend services for label storage & versioning, task assignment, QA workflows, authentication, and multi-user isolation.
- Integrate pre-labeling / pseudo-labeling outputs and instrument acceptance-rate and throughput metrics to close the auto-labeling feedback loop.
- Fuse HD map layers and priors into labeling and QC workflows.
- Create data converters and ingestion paths for multi-sensor scenes (LiDARs, cameras, calibration) to platform formats.
- Deliver dataset exports with lineage and auditability required for downstream ML training and safety validation.
- Use AWS and Databricks-adjacent tooling to host scene data and deploy scalable services.
- Collaborate closely with Data Annotation, Autonomy/ML, Scene Selection, Mapping, and Data Engineering to align the platform with real workflows.
- Participate in agile ceremonies, sprint planning, and demos; contribute to code reviews, documentation, and hardening prototypes into production systems.
- Identify and remediate technical debt, performance bottlenecks, and reliability gaps.
What You’ll Need To Succeed
- Strong proficiency in TypeScript and React; experience shipping production web applications.
- Experience with browser-based 3D graphics (three.js, WebGL) or strong graphics fundamentals.
- Proficiency in Python for backend services and APIs.
- Experience working with large sensor datasets (point clouds, imagery, video) and optimizing data-heavy UIs.
- Strong SQL skills and hands-on experience with PostgreSQL for labels, tasks, and metadata.
- Practical experience with AWS services for data hosting and service deployment.
- Proficiency with Git and GitHub for collaborative development.
- Familiarity with JIRA or similar tools for tracking work.
- Solid software engineering fundamentals: data structures, algorithms, and system design.
- Strong written and verbal communication skills; ability to collaborate with non-engineer users.
- Bachelor’s degree in Computer Science, Software Engineering, or related field — or equivalent experience.
Bonus Points
- Experience with point cloud streaming / LOD formats (Potree, COPC, 3D Tiles, LAS/LAZ).
- Prior work on annotation/labeling tools or platforms.
- Familiarity with robotics visualization ecosystems (Rerun, Foxglove, MCAP, ROS bag tooling).
- Background in perception ML workflows (detection, tracking, segmentation, auto-labeling).
- Knowledge of multi-view geometry and sensor calibration (intrinsics/extrinsics, projection, time sync).
- Experience with HD map formats (OpenDRIVE, NDS, Lanelet2) and fusing map data.
- Familiarity with PostGIS / spatial queries.
- Experience with Databricks or large-scale data processing platforms.
- Contributions to relevant open-source projects.
Perks & Compensation
- Competitive total compensation package including bonus component and stock option opportunities.
- US pay range: $139,000—$166,800 USD (annual).
- 100% paid medical, dental, and vision premiums for full-time employees.
- 401(k) plan with employer match.
- Flexible scheduling and generous paid time off.
- AD&D and life insurance.
- Potential sign-on, relocation, and other role-dependent compensation elements.
Additional Details
- Employment type: Full-time
- Job ID: 102797
Equal Opportunity & Hiring Transparency
Careertakes and our client are Equal Opportunity Employers committed to building a diverse and inclusive workforce. We prohibit discrimination or harassment of any kind. To support a fair and efficient hiring process, AI tools may be used to assist with application review or resume screening. These tools do not replace human decision-making. Final hiring decisions are made by people.
If you have questions about how your data is used, please contact us directly.
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