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.

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What You’ll Do

• Design, build, test, and deploy tooling and scalable pipelines that validate and deliver pseudo-labeled ML datasets (images, point clouds, trajectories, lane lines, segmentation, depth, etc.) to downstream consumers.
• Implement quality-control tooling and monitoring to measure pseudo-label accuracy, coverage, and pipeline health; translate findings into actionable remediation steps.
• Own the data selection and "virtual packaging" flow so online model-training systems can consume curated datasets on-demand.
• Build and evolve the ML data delivery system used by online perception teams to train and evaluate models in production-like cycles.
• Identify and eliminate throughput, quality, and reliability bottlenecks across the pseudo-labeling and data delivery stack.
• Lead projects end-to-end, mentor junior engineers, and drive alignment across cross-functional partners (perception, simulation, ops).
• Develop services, utilities, and internal APIs with disciplined software development processes (version control, CI, testing, documentation).
• Define ingestion, curation, governance, and access patterns for large, multi-modal datasets used for analytics and ML training.
• Produce data products and visualizations that improve accessibility and decision-making for internal customers.
• Evaluate new tools and architectures that improve data quality, reduce cycle time, and increase operational reliability; document standards and best practices.

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Qualifications

• Bachelor’s degree in Computer Science, Robotics, Electrical Engineering, or related technical field plus ~6+ years of relevant experience, OR Master’s degree plus ~3+ years of relevant experience.
• Strong software engineering experience building and operating large-scale data pipelines and services (Python proficiency required).
• Familiarity with offline perception workflows and pseudo-labeling best practices.
• Experience with parquet-style data processing (PyArrow, Pandas, Daft, etc.) and data curation for model training.
• MLOps experience: experiment tracking, model registry, MLflow or Weights & Biases, metrics and evaluation tooling.
• Experience with distributed data processing and ML frameworks (PyTorch, Lightning, Ray or similar).
• Production development tools: Docker, CI systems (e.g., GitHub Actions), VDI/cloud development workflows.
• Strong statistical analysis and reporting skills; ability to convert data-quality signals into prioritized engineering actions.
• Demonstrated ability to lead projects and mentor team members with minimal supervision.

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Nice-to-Haves / Bonus Points

• Prior work on large-scale data delivery systems or cataloging pipelines.
• Direct pseudo-labeling experience or familiarity with annotation workflows for AV perception.
• Experience designing systems for on-demand model training and online perception pipelines.

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Compensation & Benefits

• Hiring range (US): $160,800 — $193,000 USD (base pay). Total compensation may include bonus and equity; final offer will depend on experience, location, and other job-related factors.
• Typical benefits for full-time roles: medical/dental/vision coverage, 401(k) match, paid time off, company holidays, life/AD&D insurance, and flexible schedules.
• Additional perks and exact benefit details will be provided by the hiring organization during the interview process.

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Location & Work Model

• Job location: Ann Arbor, MI (role is listed as TELECOMMUTE / remote-friendly). Candidates must be authorized to work in the United States.
• Confidential Client will consider reasonable accommodations during the hiring process. Employment is contingent on eligibility to work in the U.S. and any required background checks consistent with applicable law.

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Legal & Process Notes

• Careertakes supports this hiring process as a third-party recruiter. The employer is Confidential Client.
• Careertakes and Confidential Client comply with all applicable U.S. employment laws. Candidates will not be asked discriminatory questions or evaluated based on protected characteristics.
• If you need a reasonable accommodation for the application/interview process, please indicate that during outreach so the recruiting team can assist.

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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.