Member of Technical Staff - ML Data
- Location
- Remote (US) · On-site
- Job type
- Full-time
- Level
- Mid-level
- Education
- Master's degree
- Listed
- 23 days ago
Skills & highlights for this role
- Python
- PyTorch
- machine learning model training
- experimental design
- distributed data processing
Also useful
- computer vision
- robotics
- distributed computing
Responsibilities
- ML Methods for Data: Design, develop, and validate ML methods for data selection, enrichment, annotation, and quality assessment.
- End-to-End Ownership: Own the full lifecycle, from problem formulation through deployment and continuous improvement.
- Large-Scale Application: Build reliable workflows for processing large-scale real-world datasets and scalable pipelines for generating synthetic data.
- Evaluation & Experimentation: Measure data quality and assess its impact on model performance.
- Iterative Improvement: Use failure analysis and feedback to improve data-processing methods.
- Annotation: Produce and evaluate labels such as captions, camera poses, depth maps, and segmentation masks.
- Research Collaboration: Partner with researchers and engineers to develop effective data solutions.
Requirements
- Master’s or Ph.D. in Computer Science, Engineering, or a related technical field, or equivalent hands-on experience.
- Demonstrated ability to develop original ML methods, evidenced by peer-reviewed publications or substantial research contributions with rigorous experimental validation.
- Experience owning the full lifecycle of an ML method: designing and implementing the approach, applying it to large-scale data, evaluating results, and improving it through successive iterations.
- Strong Python and PyTorch skills, with experience training, adapting, and evaluating machine learning models.
- Ability to design controlled experiments, establish meaningful metrics, and analyze errors to guide improvements.
- Strong software engineering skills, with an emphasis on reproducibility, reliability, and maintainable code.
Nice to Have
- Publications in computer vision, robotics, or related machine learning fields, with a substantial personal contribution.
- Experience scaling ML inference and data processing with distributed computing tools.
- Experience optimizing large-scale inference or data-processing workflows.
- Experience building and operating distributed data pipelines over hundreds of terabytes, with a strong focus on idempotency, backfills, and schema evolution.
About US
Veeda AI is building the next generation of multimodal foundation world models for Physical AI. We're a small, fast-moving team of engineers and researchers from leading AI labs, tackling some of the most challenging problems at the intersection of AI, robotics, and embodied intelligence. If you're excited about pushing the boundaries of what's possible with Physical AI, you'll have the opportunity to make an outsized impact from day one.
From Veeda AI's careers page, first listed on Rolev.ai on October 17, 2026. Rolev.ai is not the employer.
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Common questions
Where is the Member of Technical Staff - ML Data job at Veeda AI located?
Yes, this Member of Technical Staff - ML Data opening at Veeda AI is listed as Remote (US) (On-site). Always check Veeda AI's application page for specific state eligibility or relocation policies.
What qualifications are required for Member of Technical Staff - ML Data at Veeda AI?
For the Member of Technical Staff - ML Data role, Veeda AI highlights a master's degree; experience with Python, PyTorch, machine learning model training, experimental design, distributed data processing. Rolev.ai can score your existing resume against these requirements and show any skill gaps before you apply.
How do I apply for the Member of Technical Staff - ML Data position at Veeda AI?
This listing links directly to Veeda AI's Ashby application page. You can apply directly on Veeda AI's site, or use Rolev.ai to check your resume fit, generate a zero-hallucination tailored resume and cover letter for this posting, and autofill the Ashby application form in 1 click with the Rolev.ai Chrome extension. You always review the form and press Submit yourself.