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Senior Machine Learning Engineer – VLA

Bonsai Robotics · San Jose, CA, United States · On Site · Active · $150,000–$200,000 / year · Rippling ATS

Job facts

FieldValue
CompanyBonsai Robotics
TitleSenior Machine Learning Engineer – VLA
Normalized title-
Department / teamSoftware Engineering
LocationSan Jose, CA, United States
Work modelOn Site
Employment typeFull Time
Salary$150,000–$200,000 / year
Statusactive
ATS providerRippling ATS
Posted / first seen2026-03-27 / 2026-05-29
Changed / last seen2026-06-06 / 2026-06-06

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ATS provider jobsActive postings observed through Rippling ATS.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in San Jose.Open
Department jobsActive postings in Software Engineering.Open
Work model jobsActive On Site postings.Open
Lifecycle eventsOpen, update, close, and reopen events for this posting.Open
Original postingCanonical source or apply URL captured from the ATS.Open

Linked records

CompanyBonsai Robotics
Source8c01e6bc-fe4f-4d9c-98eb-2a3758bfbfed
ATS providerRippling ATS

Description

company About Bonsai Robotics Bonsai Robotics develops affordable, vision-based autonomy that makes off-road equipment smarter, safer, and more productive. We are redefining outdoor autonomy with Bonsai Intelligence, a connected platform that's inspired by biology to see, think, and act with precision like a human. We bring together advanced perception, embodied AI, integrations with equipment manufacturers, and our compact, modular Amiga vehicles to deliver reliable automation to the world's most demanding field operations—reducing costs and increasing operational efficiencies. role About the role We're looking for a Machine Learning Engineer who can own the full lifecycle of training and deploying end-to-end Vision-Language-Action (VLA) models for outdoor autonomy. You'll build the models that allow any vehicle—from our Amiga platform to heavy off-road equipment—to navigate, act, and adapt in unstructured outdoor environments using raw sensor inputs (cameras, IMU, GPS, LiDAR, and more). We have collected a large dataset of heavy equipment working in the field from deployments and are looking for people who can leverage massive real-world data as well as data from targeted data collection to train a VLA model. This is a high-impact, end-to-end role: you'll touch everything from data pipelines and model architecture to real-world deployment on edge hardware. What you'll do Design, train, and iterate on VLA and other learned behavior policy architectures for vehicle control in diverse outdoor environments Build and maintain robust data pipelines—ingestion, curation, labeling, and versioning—to support reproducible, high-quality training at scale Develop evaluation frameworks: offline metrics, simulation-based testing, and real-world field validation loops Optimize models for deployment on edge compute (NVIDIA Jetson and similar), addressing latency, memory, and throughput constraints Collaborate closely with perception, controls, platform, and field operations teams to integrate learned policies into our full autonomy stack Instrument and monitor deployed models in production, diagnosing failure modes and feeding insights back into the training loop Stay current with the rapidly evolving landscape of foundation models for robotics and bring new ideas from research into practice Qualifications 3+ years applying deep learning to real-world robotics or embodied AI problems using PyTorch, JAX, Ray, or similar frameworks 3+ years building, deploying, and maintaining ML models in production—not just research prototypes Strong practical experience with behavior cloning, reinforcement learning, or other data-driven control approaches Familiarity with multimodal model architectures (vision-language models, VLAs, or similar) Comfort working across the stack: data infrastructure, model training, optimization, and on-device deployment Experience working with real sensor data (camera, IMU, GPS, LiDAR) in noisy, unstructured environments Bonus Points For Experience with flow-matching policies, action-chunking transformers, or other recent advances in learned manipulation/navigation policies Hands-on work with TensorRT, ONNX, or other model optimization toolchains for edge deployment Published work at ICRA, IROS, CoRL, CVPR, NeurIPS, ICML, or similar venues Experience with ROS2 or robotics middleware in production systems Background in agriculture, construction, mining, or other outdoor/off-road domains Bonsai Robotics is building the future of outdoor autonomy. If you want to ship models that drive real machines in real fields—not just run on a cluster—we'd love to hear from you. Bonsai Robotics is an Equal Employment Opportunity employer and considers all qualified applicants without regard to race, color, religion, sex, sexual orientation, national origin, ancestry, age, disability, gender identity or expression, marital status, or any other legally protected status.

Full job record

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Source ID8c01e6bc-fe4f-4d9c-98eb-2a3758bfbfed
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TitleSenior Machine Learning Engineer – VLA
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Location TextSan Jose, CA, United States
DepartmentSoftware Engineering
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Remote Policy
CountryUnited States
RegionCA
CitySan Jose
Salary RawUSD 150000-200000 YEAR
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First Seen At2026-05-29 07:14:10Z
Last Seen At2026-06-06 08:44:54Z
Last Checked At2026-06-06 08:44:54Z
Last Changed At2026-06-06 08:44:54Z
Inactive At
Source Posted At2026-03-27 02:05:44Z
Source Updated At
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      "role": "<meta><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"font-size:18pt;white-space:pre-wrap;\">About the role</strong></b></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">We're looking for a Machine Learning Engineer who can own the full lifecycle of training and deploying end-to-end Vision-Language-Action (VLA) models for outdoor autonomy. You'll build the models that allow any vehicle—from our Amiga platform to heavy off-road equipment—to navigate, act, and adapt in unstructured outdoor environments using raw sensor inputs (cameras, IMU, GPS, LiDAR, and more). 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This is a high-impact, end-to-end role: you'll touch everything from data pipelines and model architecture to real-world deployment on edge hardware.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"font-size:18pt;white-space:pre-wrap;\">What you'll do</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"color:rgb(0,0,0);font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Design, train, and iterate on VLA and other learned behavior policy architectures for vehicle control in diverse outdoor environments</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Build and maintain robust data pipelines—ingestion, curation, labeling, and versioning—to support reproducible, high-quality training at scale</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Develop evaluation frameworks: offline metrics, simulation-based testing, and real-world field validation loops</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Optimize models for deployment on edge compute (NVIDIA Jetson and similar), addressing latency, memory, and throughput constraints</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Collaborate closely with perception, controls, platform, and field operations teams to integrate learned policies into our full autonomy stack</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Instrument and monitor deployed models in production, diagnosing failure modes and feeding insights back into the training loop</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Stay current with the rapidly evolving landscape of foundation models for robotics and bring new ideas from research into practice</span></li></ul><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"font-size:18pt;white-space:pre-wrap;\">Qualifications</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"color:rgb(0,0,0);font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">3+ years applying deep learning to real-world robotics or embodied AI problems using PyTorch, JAX, Ray, or similar frameworks</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">3+ years building, deploying, and maintaining ML models in production—not just research prototypes</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Strong practical experience with behavior cloning, reinforcement learning, or other data-driven control approaches</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Familiarity with multimodal model architectures (vision-language models, VLAs, or similar)</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Comfort working across the stack: data infrastructure, model training, optimization, and on-device deployment</span></li><li style=\"color:rgb(0,0,0);font-size:12pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Experience working with real sensor data (camera, IMU, GPS, LiDAR) in noisy, unstructured environments</span></li></ul><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><b><strong style=\"font-size:18pt;white-space:pre-wrap;\">Bonus Points For</strong></b></p><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;margin:8px 0px;line-height:1.6;padding:0px 0px 0px 32px;list-style-type:disc;\"><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Experience with flow-matching policies, action-chunking transformers, or other recent advances in learned manipulation/navigation policies</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Hands-on work with TensorRT, ONNX, or other model optimization toolchains for edge deployment</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Published work at ICRA, IROS, CoRL, CVPR, NeurIPS, ICML, or similar venues</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Experience with ROS2 or robotics middleware in production systems</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Background in agriculture, construction, mining, or other outdoor/off-road domains</span></li></ul><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Bonsai Robotics is building the future of outdoor autonomy. If you want to ship models that drive real machines in real fields—not just run on a cluster—we'd love to hear from you.</span></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;text-align:start;\"><span style=\"font-size:11pt;white-space:pre-wrap;\">Bonsai Robotics is an Equal Employment Opportunity employer and considers all qualified applicants without regard to race, color, religion, sex, sexual orientation, national origin, ancestry, age, disability, gender identity or expression, marital status, or any other legally protected status.</span></p>",
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            "oid": "location",
            "title": "Location (city only)",
            "required": true,
            "fieldData": {},
            "fieldType": "SHORT_ANSWER"
          },
          {
            "oid": "resume",
            "title": "Resume",
            "required": true,
            "fieldData": {},
            "fieldType": "FILE"
          },
          {
            "oid": "cover_letter",
            "title": "Cover letter",
            "required": false,
            "fieldData": {},
            "fieldType": "FILE"
          }
        ]
      },
      "additionalQuestions": null
    },
    "hasAIEvaluationsEnabled": false,
    "eeocQuestionnaireEnabled": true,
    "applicationConfirmationTemplate": "65207b0236caba8f1bad8fe4",
    "eeocQuestionnaireEnabledForJobPost": true
  },
  "detail_meta": {
    "url": "https://ats.rippling.com/api/v2/board/bonsairoboticsmain/jobs/8d5bab70-e012-42df-aedd-a76c0bb82728",
    "http_status": 200,
    "content_type": "application/json",
    "response_bytes": 14809
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  "detail_errors": []
}
Get this page with API

Rendered from the bluedoor Job Postings API. Reproduce it:

GET https://api.bluedoor.sh/job-postings/v1/jobs/8a317f8c57dcc2a193b3cb72412edd5f98ec358e?include=descriptionJSON
GET https://api.bluedoor.sh/job-postings/v1/orgs/1028aa48-fb98-4074-ad98-986d770ff8daJSON
GET https://api.bluedoor.sh/job-postings/v1/sources/8c01e6bc-fe4f-4d9c-98eb-2a3758bfbfedJSON
GET https://api.bluedoor.sh/job-postings/v1/jobs/8a317f8c57dcc2a193b3cb72412edd5f98ec358e/eventsJSON