Pay
$127K–$190K is typical
The middle half of what similar US postings state. This one doesn’t list pay.
From 2,133 postings in the last year. Stated ranges, not salaries paid.
Senior / Staff AI Research Engineer, Data Infrastructure
Milpitas, CA
Open 5 months, first seen by us 155 days ago- Pay
USD 185,000–325,000/yearAnnual period assumed. Location-specific pay — pay source
Lunches and dinners, a fully stocked kitchen, and regular team-building events. Compensation: Salary $185,000–$325,000 USD + Bonus + Equity The base salary range above represents the expected compensation for this full-time U.S. position. Final compensation will be determined based on role scope, level, location, job-related skills, experience, and relevant education or training, and may fall outside the listed range in exceptional cases.
Read the full posting- Work setting
- Not stated
- Employment
- Not stated
Before you apply
- Work authorization
- Sponsors visas
What you’ll work on
Full postingDesign and maintain data collection pipelines for teleoperation and UMI demonstration data
Build annotation tooling and curation workflows: filtering, deduplication, episode scoring
Develop post-SFT reinforcement learning infrastructure with reward scoring and failure mining
Build evaluation infrastructure to log on-robot policy rollouts and surface diagnostics
Architect storage and retrieval for heterogeneous robot data across cloud and on-prem
From the employer’s posting
Design and maintain end-to-end data collection pipelines ingesting multimodal demonstration data from teleoperation devices and UMI hardware
Build annotation tooling and data curation workflows — quality filtering, deduplication, episode scoring, and domain reweighting
Develop post-SFT reinforcement learning infrastructure: implement reward scoring on demonstrations, mine and categorize failure patterns
Build evaluation and test infrastructure to log policy rollouts on-robot, capture structured results, and surface actionable diagnostics for the research team
Architect scalable storage and retrieval systems for heterogeneous robot data (vision, proprioception, action, language) across both cloud and on-prem environments.
What you’ll bring
All qualificationsCore experience
- Bachelor's or Master's degree in Computer Science, Robotics, or related field with 5+ years of experience.
- Experience with robotics data collection hardware — teleoperation devices, UMI, GELLO, or similar — and the synchronization and preprocessing challenges they introduce.
- Strong proficiency in Python and experience building production-grade data pipelines and ETL systems.
- Familiarity with robot learning pipelines: imitation learning, behavior cloning, or VLA/VLM fine-tuning workflows.
- Hands-on experience with large-scale dataset management, including versioning, deduplication, quality filtering, and distributed storage (e.g., S3, GCS, HDF5, WebDataset, Zarr).
- Experience building evaluation or experiment tracking infrastructure (e.g., Weights & Biases, MLflow, custom rollout loggers).
Qualification wording
Bachelor's or Master's degree in Computer Science, Robotics, or related field with 5+ years of experience.
Experience with robotics data collection hardware — teleoperation devices, UMI, GELLO, or similar — and the synchronization and preprocessing challenges they introduce.
Strong proficiency in Python and experience building production-grade data pipelines and ETL systems.
Familiarity with robot learning pipelines: imitation learning, behavior cloning, or VLA/VLM fine-tuning workflows.
Hands-on experience with large-scale dataset management, including versioning, deduplication, quality filtering, and distributed storage (e.g., S3, GCS, HDF5, WebDataset, Zarr).
Experience building evaluation or experiment tracking infrastructure (e.g., Weights & Biases, MLflow, custom rollout loggers).
Education & alternatives
Requirements - Bachelor's or Master's degree in Computer Science, Robotics, or related field with 5+ years of experience. - Strong proficiency in Python and experience building production-grade data pipelines and ETL systems.
Benefits in the posting
Full benefits wording- Competitive stock options/equity programs.
- Health, dental, and vision insurance, 401(k) plan.
- Visa sponsorship and green card support for qualified candidates.
From the employer’s posting.
Posting record
Report an errorOpen 5 monthsWe first saw this posting 155 days ago and it is still up. Roles open this long are often slow to fill or kept open to collect applications.
- Status in our records
- Live
- First seen by us
- Jun 2, 2026155 days ago
- Recorded sightings
- 58
- Last seen by us
- Nov 3, 2026
These dates show when we found the posting. Check the employer’s website to confirm it is still accepting applications.
How this job compares
Time since we first saw it
Day 155
Up longer than most. Similar jobs usually come down between day 5 and day 54.
From 10,736 similar postings that came down. Coming down is not always a hire.
RoboForce is hiring
2 open jobs
Open jobs by the week we first saw them, last 12 weeks.
Hiring recordSee how this role fits your experience
Add your resume and we’ll mark which of these tools you already use, and point out anything in the posting that could rule you out.
- Python
- Google Cloud Storage
- MLflow
- S3
- PyTorch
Where the posting names them
- Bachelor's or Master's degree in Computer Science, Robotics, or related field with 5+ years of experience. - Strong proficiency in Python and experience building production-grade data pipelines and ETL systems. - Hands-on experience with large-scale dataset management, including versioning, deduplication, quality filtering, and distributed storage (e.g., S3, GCS, HDF5, WebDataset, Zarr).
- Strong proficiency in Python and experience building production-grade data pipelines and ETL systems. - Hands-on experience with large-scale dataset management, including versioning, deduplication, quality filtering, and distributed storage (e.g., S3, GCS, HDF5, WebDataset, Zarr). - Experience building or working with post-training infrastructure — SFT pipelines, reward modeling, or RL training loops (e.g., PPO, DPO, rejection sampling).
- Familiarity with robot learning pipelines: imitation learning, behavior cloning, or VLA/VLM fine-tuning workflows. - Experience building evaluation or experiment tracking infrastructure (e.g., Weights & Biases, MLflow, custom rollout loggers). - Proven ability to design annotation tooling or human-in-the-loop labeling systems for structured or multimodal data.
- Experience building or working with post-training infrastructure — SFT pipelines, reward modeling, or RL training loops (e.g., PPO, DPO, rejection sampling). - Familiarity with deep learning frameworks (PyTorch, JAX) and ML training workflows sufficient to collaborate tightly with research teams. - Requires 5 days/week in-office collaboration with the teams.
Your next step
Complete your application on job-boards.greenhouse.io. The employer’s form will show what is required.
Applying through Greenhouse
- No account needed: the form is one page, with an “Autofill my application” option that reads your resume.
- Greenhouse doesn’t read resumes over 2.5 MB, or details placed in a header, footer, text box, table or second column. The file still attaches, but a recruiter has to type you in by hand.
Already applied? Track this application
About the role
We file this job under Data Engineer, by the work the posting describes.
Data engineers build and run the pipelines that copy data out of apps and outside services into a warehouse or lake, and fix them when a source changes or a load fails.
Expect SQL, Python, a cloud platform, a scheduler such as Airflow, and often tools for large data such as Spark or Kafka.
An analytics engineer works one step later, turning the raw data a data engineer lands into clean tables people can query.
US government figures for database architects
- Median yearly pay, May 2025
- $139,500
- Expected change, 2025 to 2035
- 9.4% more jobsagainst 3.5% for all jobs
The government has no code for data engineers, so these figures are for the closest group, database architects, which includes data integration and data warehousing specialists.
Source: US Bureau of Labor Statistics, Occupational Employment and Wage Statistics (May 2025) and Employment Projections (2025 to 2035). Occupation code 15-1243.
Job description
Why RoboForce
RoboForce is an AI robotics company developing Physical AI–powered Robo-Labor for dull, dirty, and dangerous work. The company's robots are engineered for demanding industrial environments, with a focus on real-world deployment and scalability.
We are looking for a Senior / Staff AI Research Engineer, Data Infrastructure to build the data and learning engine behind RoboForce's Physical AI stack. In this role, you will own the full pipeline — from raw teleoperation and UMI device data collection through curation, annotation, and storage, to post-training infrastructure that scores demonstrations, identifies failure patterns, and closes the loop back into model retraining.
Responsibilities
-
Design and maintain end-to-end data collection pipelines ingesting multimodal demonstration data from teleoperation devices and UMI hardware, including synchronization, versioning, and distributed storage at scale.
-
Build annotation tooling and data curation workflows — quality filtering, deduplication, episode scoring, and domain reweighting — to produce high-quality training datasets for robot policy learning.
-
Develop post-SFT reinforcement learning infrastructure: implement reward scoring on demonstrations, mine and categorize failure patterns, and feed curated failure data back into the retraining loop.
-
Build evaluation and test infrastructure to log policy rollouts on-robot, capture structured results, and surface actionable diagnostics for the research team.
-
Collaborate with ML researchers to define data schemas, episode formats, and pipeline interfaces that support rapid iteration on VLA and manipulation policy training.
-
Architect scalable storage and retrieval systems for heterogeneous robot data (vision, proprioception, action, language) across both cloud and on-prem environments.
Requirements
-
Bachelor's or Master's degree in Computer Science, Robotics, or related field with 5+ years of experience.
-
Strong proficiency in Python and experience building production-grade data pipelines and ETL systems.
-
Hands-on experience with large-scale dataset management, including versioning, deduplication, quality filtering, and distributed storage (e.g., S3, GCS, HDF5, WebDataset, Zarr).
-
Experience building or working with post-training infrastructure — SFT pipelines, reward modeling, or RL training loops (e.g., PPO, DPO, rejection sampling).
-
Familiarity with deep learning frameworks (PyTorch, JAX) and ML training workflows sufficient to collaborate tightly with research teams.
-
Requires 5 days/week in-office collaboration with the teams.
Bonus Qualifications
-
Experience with robotics data collection hardware — teleoperation devices, UMI, GELLO, or similar — and the synchronization and preprocessing challenges they introduce.
-
Familiarity with robot learning pipelines: imitation learning, behavior cloning, or VLA/VLM fine-tuning workflows.
-
Experience building evaluation or experiment tracking infrastructure (e.g., Weights & Biases, MLflow, custom rollout loggers).
-
Proven ability to design annotation tooling or human-in-the-loop labeling systems for structured or multimodal data.
Benefits
-
Competitive stock options/equity programs.
-
Health, dental, and vision insurance, 401(k) plan.
-
Visa sponsorship and green card support for qualified candidates.
-
Lunches and dinners, a fully stocked kitchen, and regular team-building events.
Compensation: Salary $185,000–$325,000 USD + Bonus + Equity
The base salary range above represents the expected compensation for this full-time U.S. position. Final compensation will be determined based on role scope, level, location, job-related skills, experience, and relevant education or training, and may fall outside the listed range in exceptional cases.
Source details
Source notes
Source excerptsSelected passages from the saved posting. Check the full description for conditions and exceptions.
- Pay
Lunches and dinners, a fully stocked kitchen, and regular team-building events. Compensation: Salary $185,000–$325,000 USD + Bonus + Equity The base salary range above represents the expected compensation for this full-time U.S. position. Final compensation will be determined based on role scope, level, location, job-related skills, experience, and relevant education or training, and may fall outside the listed range in exceptional cases.
- Location & working pattern
Milpitas, CA
Working pattern and location restrictions need checking in the full posting.
- Work authorization
- Health, dental, and vision insurance, 401(k) plan. - Visa sponsorship and green card support for qualified candidates. - Lunches and dinners, a fully stocked kitchen, and regular team-building events.