Home › Companies › Luminary › AI/ML Scientist Lead Engineer
AI/ML Scientist Lead Engineer
Luminary · San Mateo, CA, United States · On Site · Active · Rippling ATS
Job facts
| Field | Value |
|---|---|
| Company | Luminary |
| Title | AI/ML Scientist Lead Engineer |
| Normalized title | - |
| Department / team | Product Engineering |
| Location | San Mateo, CA, United States |
| Work model | On Site |
| Employment type | Full Time |
| Salary | - |
| Status | active |
| ATS provider | Rippling ATS |
| Posted / first seen | 2026-04-02 / 2026-05-29 |
| Changed / last seen | 2026-06-06 / 2026-06-06 |
Related slices
| Page | What it contains | Open |
|---|---|---|
| Company jobs | Active postings from Luminary. | Open |
| Company breakdowns | Role, location, ATS, and work model facets for this company. | Open |
| ATS provider jobs | Active postings observed through Rippling ATS. | Open |
| Provider filtered search | The same provider as a filtered job collection. | Open |
| City jobs | Active postings in San Mateo. | Open |
| Department jobs | Active postings in Product Engineering. | Open |
| Work model jobs | Active On Site postings. | Open |
| Lifecycle events | Open, update, close, and reopen events for this posting. | Open |
| Original posting | Canonical source or apply URL captured from the ATS. | Open |
Linked records
| Company | Luminary |
| Source | d0e4f0f8-3ac3-4025-84fe-26225ec1fd79 |
| ATS provider | Rippling ATS |
Description
company
Luminary helps engineering companies be more competitive by getting to market faster, creating new, better products, and reducing development risk. We do this with our Physics AI platform, the fastest and easiest way to build and deploy models to understand and instantly predict physical reality with precision. Customers span industries from automotive and aerospace, to leading sporting equipment providers, including Otto Aviation, Joby Aviation, Piper Aircraft and Trek Bikes. Luminary is a Series B company and is headquartered in San Mateo, California.
role
The Role We're looking for a visionary Physics AI leader to drive our vision for Physics AI. This role is a player-coach who will lead the Physics AI team at Luminary, while contributing concrete ideas and product architecture to drive the delivery of Physics AI foundation models. The role is responsible for driving how Luminary changes customer engineering design workflows forever
Responsibilities Develop Physics-AI Tooling: Architect and implement high-performance tools for physics-informed workflows, similar in scope and capability to NVIDIA Modulus/Physics-ML (formerly Physics-Nemo) , ensuring the delivery of models built off of synthetic data Foundation Model Research: Lead the development of large-scale foundation models for the physical sciences, inspired by the collaborative, cross-domain approach of initiatives like Polymathic AI . Architectural Innovation: Design and optimize specialized neural architectures for multi-scale physical systems, e.g. AB-UPT and related operator learning methods. Physics-Informed Machine Learning (PIML): Embed physical constraints (conservation laws, symmetries, and PDEs) directly into the loss functions and inductive biases of deep learning models to ensure physical consistency and data efficiency. Scalable Engineering: Collaborate with software engineers to deploy these models at scale within the Luminary Cloud platform, enabling real-time or near-real-time simulation for complex CFD/FEA problems. Leadership: Drive the deliverables of the physics AI team each quarter contributing to the larger Luminary platform
Qualifications Required Masters degree or higher in Computer Science, Mechanical Engineering, Aerospace Engineering, or related field 5+ years of experience building production software or ML systems Experience with Physics Nemo models such as Domino and GeoTransolver Experience with Geometry processing, Meshing, and physics solvers a must Familiarity with developing LLM-powered applications a plus Strong proficiency in Python Proficiency using coding agents such as Claude Code Familiarity with Physics AI, CAE, or physics simulation domains a critical requirement Experience with distributed ML applications a big plus
What we are not looking for Not looking for a pure manager for this role Not looking for someone who has no background in Physics
Full job record
| Job ID | 63e106464c8f8e9f940ad5b427422637d905247f |
| Org ID | 1853f183-e71d-4772-a2b4-7acccd0e77f4 |
| Source ID | d0e4f0f8-3ac3-4025-84fe-26225ec1fd79 |
| Board ID | d0e4f0f8-3ac3-4025-84fe-26225ec1fd79 |
| Provider | rippling |
| Provider Job Key | cf35e7be-91f9-40f1-b054-d47427534f3c |
| Title | AI/ML Scientist Lead Engineer |
| Normalized Title | — |
| Status | active |
| Active | yes |
| Location Text | San Mateo, CA, United States |
| Department | Product Engineering |
| Team | — |
| Employment Type | full_time |
| Workplace Type | on_site |
| Remote Policy | — |
| Country | United States |
| Region | CA |
| City | San Mateo |
| Salary Raw | — |
| Salary Min | — |
| Salary Max | — |
| Salary Currency | — |
| Salary Period | — |
| Source URL | https://ats.rippling.com/luminarycloud/jobs/cf35e7be-91f9-40f1-b054-d47427534f3c |
| Apply URL | https://ats.rippling.com/luminarycloud/jobs/cf35e7be-91f9-40f1-b054-d47427534f3c |
| First Seen At | 2026-05-29 07:12:51Z |
| Last Seen At | 2026-06-06 08:46:23Z |
| Last Checked At | 2026-06-06 08:46:23Z |
| Last Changed At | 2026-06-06 08:46:23Z |
| Inactive At | — |
| Source Posted At | 2026-04-02 23:57:13Z |
| Source Updated At | — |
| Raw Payload Uri | s3://job-postings-prod-raw-590183727216/raw/provider=rippling/board=luminarycloud/date=2026-06-06/2026-06-06T08-46-21-850Z-909b09de43f3d2ebc4b0956897198a40b0f809bb71d46d82378a60a8881919aa.json |
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The role is responsible for driving how Luminary changes customer engineering design workflows forever</span></p><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><hr><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><h2 style=\"font-family:"Basel Grotesk",Arial,sans-serif;line-height:1.6;font-size:29pt;font-weight:600;letter-spacing:0.5px;margin-top:18px;margin-bottom:4px;padding-left:0px;\"><span style=\"color:rgb(0,0,0);font-size:16pt;white-space:pre-wrap;\">Responsibilities</span></h2><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:"Basel Grotesk",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;\"><b><strong style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Develop Physics-AI Tooling:</strong></b><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\"> Architect and implement high-performance tools for physics-informed workflows, similar in scope and capability to </span><b><strong style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">NVIDIA Modulus/Physics-ML (formerly Physics-Nemo)</strong></b><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">, ensuring the delivery of models built off of synthetic data</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;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;\">Foundation Model Research:</strong></b><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\"> Lead the development of large-scale foundation models for the physical sciences, inspired by the collaborative, cross-domain approach of initiatives like </span><b><strong style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Polymathic AI</strong></b><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;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;\">Architectural Innovation:</strong></b><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\"> Design and optimize specialized neural architectures for multi-scale physical systems, e.g.</span><b><strong style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">AB-UPT</strong></b><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\"> and related operator learning methods.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;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;\">Physics-Informed Machine Learning (PIML):</strong></b><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\"> Embed physical constraints (conservation laws, symmetries, and PDEs) directly into the loss functions and inductive biases of deep learning models to ensure physical consistency and data efficiency.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;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;\">Scalable Engineering:</strong></b><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\"> Collaborate with software engineers to deploy these models at scale within the Luminary Cloud platform, enabling real-time or near-real-time simulation for complex CFD/FEA problems.</span></li><li style=\"color:rgb(0,0,0);font-size:11pt;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;\">Leadership: </strong></b><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Drive the deliverables of the physics AI team each quarter contributing to the larger Luminary platform</span></li></ul><p style=\"font-family:"Basel Grotesk",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:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><hr><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br></p><h2 style=\"font-family:"Basel Grotesk",Arial,sans-serif;line-height:1.6;font-size:29pt;font-weight:600;letter-spacing:0.5px;margin-top:18px;margin-bottom:4px;padding-left:0px;\"><span style=\"color:rgb(0,0,0);font-size:16pt;white-space:pre-wrap;\">Qualifications</span></h2><h3 style=\"font-family:"Basel Grotesk",Arial,sans-serif;line-height:1.6;font-size:21pt;font-weight:600;letter-spacing:0.25px;margin-top:14px;margin-bottom:4px;padding-left:0px;\"><span style=\"color:rgb(67,67,67);font-size:14pt;white-space:pre-wrap;\">Required</span></h3><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:"Basel Grotesk",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;\">Masters degree or higher in Computer Science, Mechanical Engineering, Aerospace Engineering, or related field</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;\">5+ years of experience building production software or ML systems</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 Physics Nemo models such as Domino and GeoTransolver</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 Geometry processing, Meshing, and physics solvers a must</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;\">Familiarity with developing LLM-powered applications a plus</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;\">Strong proficiency in </span><b><strong style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Python</strong></b></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;\">Proficiency using coding agents such as Claude Code</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;\">Familiarity with </span><b><strong style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\">Physics AI, CAE, or physics simulation</strong></b><span style=\"color:rgb(0,0,0);font-size:11pt;white-space:pre-wrap;\"> domains a critical requirement</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 distributed ML applications a big plus</span></li></ul><p style=\"font-family:"Basel Grotesk",Arial,sans-serif;font-size:11pt;font-weight:400;line-height:1.6;letter-spacing:0.25px;margin:4px 0px;padding:0px;\"><br><br></p><h3 style=\"font-family:"Basel Grotesk",Arial,sans-serif;line-height:1.6;font-size:21pt;font-weight:600;letter-spacing:0.25px;margin-top:14px;margin-bottom:4px;padding-left:0px;\"><span style=\"color:rgb(67,67,67);font-size:14pt;white-space:pre-wrap;\">What we are not looking for</span></h3><ul data-pattern=\"discCircleSquare\" data-depth=\"1\" style=\"font-family:"Basel Grotesk",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;\">Not looking for a pure manager for this role</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;\">Not looking for someone who has no background in Physics</span></li></ul>",
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}Get this page with API
Rendered from the bluedoor Job Postings API. Reproduce it:
GET https://api.bluedoor.sh/job-postings/v1/jobs/63e106464c8f8e9f940ad5b427422637d905247f?include=descriptionJSONGET https://api.bluedoor.sh/job-postings/v1/orgs/1853f183-e71d-4772-a2b4-7acccd0e77f4JSONGET https://api.bluedoor.sh/job-postings/v1/sources/d0e4f0f8-3ac3-4025-84fe-26225ec1fd79JSONGET https://api.bluedoor.sh/job-postings/v1/jobs/63e106464c8f8e9f940ad5b427422637d905247f/eventsJSON