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Senior Machine Learning Engineer

Kinetic Automation Inc. · Costa Mesa, CA, United States · On Site · Active · Rippling ATS

Job facts

FieldValue
CompanyKinetic Automation Inc.
TitleSenior Machine Learning Engineer
Normalized title-
Department / teamEngineering
LocationCosta Mesa, CA, United States
Work modelOn Site
Employment typeFull Time
Salary-
Statusactive
ATS providerRippling ATS
Posted / first seen2026-05-11 / 2026-05-29
Changed / last seen2026-06-06 / 2026-06-06

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City jobsActive postings in Costa Mesa.Open
Department jobsActive postings in Engineering.Open
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Linked records

CompanyKinetic Automation Inc.
Source0baa9d8e-db2b-4772-8150-abe6a0bb58f5
ATS providerRippling ATS

Description

company About Kinetic Kinetic Automation is building a network of automated repair centers for modern vehicles. The auto industry is transitioning from mechanically complex vehicles to mechanically simple ones with complex software and technology. Kinetic aims to be the primary infrastructure-as-a-service for servicing future vehicles with our robotic repair centers, powered by our proprietary software and AI. We are a strong team of experienced robotics + automotive + shared mobility enthusiasts who have worked in self-driving, mapping, lidar, motorsport, and ride-sharing. We are a venture backed startup (Series B) with a clear go-to-market strategy and meaningful revenue. role About the role You will be a part of a small, production-minded ML team based in Orange County/Oakland. You’ll collaborate with other engineers and researchers to develop, evaluate, and help deploy vision models for tasks like semantic/instance segmentation and object/damage detection across 2D and 3D data. Experience & Skills Required Deep ML / CV Fundamentals: You need hands-on experience training and evaluating deep models for segmentation and detection (PyTorch). You must understand how Transformer/LLM building blocks map to vision (ViT/DETR/Mask2Former) and have practical exposure to 2D/3D data, point clouds, and camera geometry Curiosity & Strict Attention to Detail: You are obsessed with corner cases. You have a sharp eye for data anomalies, run rigorous ablations, keep meticulous experiment logs, and can clearly communicate trade-offs AI-Empowered, Not AI-Dependent: We strongly encourage leveraging AI tools (Copilot, ChatGPT, Claude) to maximize your efficiency. However, you must 100% understand the underlying details of the code you ship. We are looking for strong independent thinkers and debuggers, not someone who simply passes along AI outputs without deep comprehension Working knowledge of transformer and LLM building blocks applied to vision, including self-attention, positional encodings, tokenization, and mapping these ideas to vision models (e.g., ViT, DETR, Mask2Former) Practical exposure to 3D/depth data, including familiarity with point clouds, camera geometry (intrinsics/extrinsics), basic calibration, and multi-view geometry Proficiency in Python and the relevant tech stack: PyTorch, torchvision, Detectron2 or MMDetection/Segmentation, and Hugging Face Transformers Experience with Python services (FastAPI/Flask), Docker, and AWS services (S3, Batch/EC2, ECR) is preferred. Strong communication skills with the ability to write tidy PRs, experiment logs, and short design notes to ensure reproducibility Responsibilities The Work: Implement training loops, curate datasets, drive high-priority experiments, and partner with cross-functional teams to close feedback loops from edge cases The Stack: PyTorch, Detectron2 / MMDetection / Segmentation, Hugging Face Transformers, Python (FastAPI), Docker, AWS Collaborate on model development by implementing training loops, losses, augmentations, and evaluations using PyTorch Keep current with the industry by summarizing relevant papers and PRs, and proposing small, testable improvements Contribute to datasets by helping define labeling guidelines, curating splits, running quality checks, and maintaining data versioning Run experiments to track metrics, perform ablations, write clear experiment notes, and present findings. Provide production support by exporting models, writing basic inference code, adding tests, and assisting with performance profiling Work cross-functionally, partnering with backend engineers on APIs, containers, and CI, and with ops/labeling teams on edge cases and feedback loops Benefits Competitive salary and equity package Comprehensive health and dental insurance Retirement savings plan. Paid time off and holidays Kinetic is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, gender, gender expression, age, national origin, disability, marital status, sexual orientation, military status, or any protected attribute. We encourage qualified candidates from all backgrounds to apply and join us in our mission. If you require accommodation at any stage of the application process due to a disability, please let us know.

Full job record

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DepartmentEngineering
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CountryUnited States
RegionCA
CityCosta Mesa
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Apply URLhttps://ats.rippling.com/kinetic/jobs/afab2e8b-6b01-4482-98d3-62d918ffcbdd
First Seen At2026-05-29 07:09:29Z
Last Seen At2026-06-06 19:04:01Z
Last Checked At2026-06-06 19:04:01Z
Last Changed At2026-06-06 19:04:01Z
Inactive At—
Source Posted At2026-05-11 20:45:31Z
Source Updated At—
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      "role": "<meta><h1 style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;line-height:1.6;font-size:18pt;font-weight:600;letter-spacing:1px;margin-top:24px;margin-bottom:4px;padding-left:0px;\"><b><strong style=\"white-space:pre-wrap;\">About the role</strong></b></h1><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:10.5pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;text-align:start;\"><span style=\"white-space:pre-wrap;\">You will be a part of a small, production-minded ML team based in Orange County/Oakland. You’ll collaborate with other engineers and researchers to develop, evaluate, and help deploy vision models for tasks like semantic/instance segmentation and object/damage detection across 2D and 3D data.</span></p><h3 style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;line-height:1.6;font-size:14pt;font-weight:600;letter-spacing:0.25px;margin-top:14px;margin-bottom:4px;text-align:start;padding-left:0px;\"><b><strong style=\"white-space:pre-wrap;\">Experience &amp; Skills Required</strong></b></h3><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=\"font-size:11pt;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><b><strong style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Deep ML / CV Fundamentals:</strong></b><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\"> You need hands-on experience training and evaluating deep models for segmentation and detection (PyTorch). You must understand how Transformer/LLM building blocks map to vision (ViT/DETR/Mask2Former) and have practical exposure to 2D/3D data, point clouds, and camera geometry</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;\"><b><strong style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Curiosity &amp; Strict Attention to Detail:</strong></b><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\"> You are obsessed with corner cases. You have a sharp eye for data anomalies, run rigorous ablations, keep meticulous experiment logs, and can clearly communicate trade-offs</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;\"><b><strong style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">AI-Empowered, Not AI-Dependent:</strong></b><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\"> We strongly encourage leveraging AI tools (Copilot, ChatGPT, Claude) to maximize your efficiency. However, you must 100% understand the underlying details of the code you ship. We are looking for strong independent thinkers and debuggers, not someone who simply passes along AI outputs without deep comprehension</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=\"white-space:pre-wrap;\">Working knowledge of transformer and LLM building blocks applied to vision, including self-attention, positional encodings, tokenization, and mapping these ideas to vision models (e.g., ViT, DETR, Mask2Former)</span></li></ul><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=\"font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Practical exposure to 3D/depth data, including familiarity with point clouds, camera geometry (intrinsics/extrinsics), basic calibration, and multi-view geometry</span></li><li style=\"font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Proficiency in Python and the relevant tech stack: PyTorch, torchvision, Detectron2 or MMDetection/Segmentation, and Hugging Face Transformers</span></li><li style=\"font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Experience with Python services (FastAPI/Flask), Docker, and AWS services (S3, Batch/EC2, ECR) is preferred.</span></li><li style=\"font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Strong communication skills with the ability to write tidy PRs, experiment logs, and short design notes to ensure reproducibility</span></li></ul><h3 style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;line-height:1.6;font-size:14pt;font-weight:600;letter-spacing:0.25px;margin-top:14px;margin-bottom:4px;text-align:start;padding-left:0px;\"><b><strong style=\"white-space:pre-wrap;\">Responsibilities</strong></b></h3><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;--listitem-marker-color:#000000;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;\"><b><strong style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">The Work:</strong></b><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\"> Implement training loops, curate datasets, drive high-priority experiments, and partner with cross-functional teams to close feedback loops from edge cases</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;\"><b><strong style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">The Stack:</strong></b><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\"> PyTorch, Detectron2 / MMDetection / Segmentation, Hugging Face Transformers, Python (FastAPI), Docker, AWS</span></li></ul><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=\"font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Collaborate on model development by implementing training loops, losses, augmentations, and evaluations using PyTorch</span></li><li style=\"font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Keep current with the industry by summarizing relevant papers and PRs, and proposing small, testable improvements</span></li><li style=\"font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Contribute to datasets by helping define labeling guidelines, curating splits, running quality checks, and maintaining data versioning</span></li><li style=\"font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Run experiments to track metrics, perform ablations, write clear experiment notes, and present findings.</span></li><li style=\"font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Provide production support by exporting models, writing basic inference code, adding tests, and assisting with performance profiling</span></li><li style=\"font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Work cross-functionally, partnering with backend engineers on APIs, containers, and CI, and with ops/labeling teams on edge cases and feedback loops</span></li></ul><h3 style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;line-height:1.6;font-size:14pt;font-weight:600;letter-spacing:0.25px;margin-top:14px;margin-bottom:4px;text-align:start;padding-left:0px;\"><b><strong style=\"white-space:pre-wrap;\">Benefits</strong></b></h3><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=\"font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Competitive salary and equity package</span></li><li style=\"font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Comprehensive health and dental insurance</span></li><li style=\"font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Retirement savings plan.</span></li><li style=\"font-size:11pt;margin:3px 0px;letter-spacing:0.25px;line-height:1.6;text-align:start;\"><span style=\"white-space:pre-wrap;\">Paid time off and holidays</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:10.5pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;text-align:start;\"><span style=\"white-space:pre-wrap;\">Kinetic is an equal opportunity employer. We celebrate diversity and are committed to creating an inclusive environment for all employees. We do not discriminate based on race, color, religion, gender, gender expression, age, national origin, disability, marital status, sexual orientation, military status, or any protected attribute. We encourage qualified candidates from all backgrounds to apply and join us in our mission. If you require accommodation at any stage of the application process due to a disability, please let us know.</span></p>",
      "company": "<meta><h1 style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;line-height:1.6;font-size:18pt;font-weight:600;letter-spacing:1px;margin-top:24px;margin-bottom:4px;padding-left:0px;\"><b><strong style=\"white-space:pre-wrap;\">About Kinetic</strong></b></h1><p style=\"font-family:&quot;Basel Grotesk&quot;,Arial,sans-serif;font-size:11.25pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><span style=\"white-space:pre-wrap;\">Kinetic Automation is building a network of automated repair centers for modern vehicles. The auto industry is transitioning from mechanically complex vehicles to mechanically simple ones with complex software and technology. Kinetic aims to be the primary infrastructure-as-a-service for servicing future vehicles with our robotic repair centers, powered by our proprietary software and AI. We are a strong team of experienced robotics + automotive + shared mobility enthusiasts who have worked in self-driving, mapping, lidar, motorsport, and ride-sharing. We are a venture backed startup (Series B) with a clear go-to-market strategy and meaningful revenue.</span></p>"
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            "fieldType": "PRONOUN"
          },
          {
            "oid": "current_company",
            "title": "Current company",
            "required": false,
            "fieldData": {},
            "fieldType": "SHORT_ANSWER"
          },
          {
            "oid": "phone_number",
            "title": "Phone number",
            "required": true,
            "fieldData": {},
            "fieldType": "PHONE_NUMBER"
          },
          {
            "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": "663e7cde2f55b9f4f5f06a5c",
    "eeocQuestionnaireEnabledForJobPost": true
  },
  "detail_meta": {
    "url": "https://ats.rippling.com/api/v2/board/kinetic/jobs/afab2e8b-6b01-4482-98d3-62d918ffcbdd",
    "http_status": 200,
    "content_type": "application/json",
    "response_bytes": 15753
  },
  "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/39939be2e3d7a33cc6528c95c8c904ebb2da10fd?include=descriptionJSON
GET https://api.bluedoor.sh/job-postings/v1/orgs/cc334c10-fa14-4ac6-9623-73d3d7d5d6c1JSON
GET https://api.bluedoor.sh/job-postings/v1/sources/0baa9d8e-db2b-4772-8150-abe6a0bb58f5JSON
GET https://api.bluedoor.sh/job-postings/v1/jobs/39939be2e3d7a33cc6528c95c8c904ebb2da10fd/eventsJSON

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