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HomeCompaniesPlus 2Senior Machine Learning Engineer, Simulation

Senior Machine Learning Engineer, Simulation

Plus 2 · Santa Clara, CA · Hybrid · Active · $130,000–$200,000 / year · Lever

Job facts

FieldValue
CompanyPlus 2
TitleSenior Machine Learning Engineer, Simulation
Normalized title-
Department / teamUS Engineering / Simulation
LocationSanta Clara, CA, United States
Work modelHybrid / Hybrid
Employment typeFull Time
Salary$130,000–$200,000 / year
Statusactive
ATS providerLever
Posted / first seen2024-11-27 / 2026-05-29
Changed / last seen2026-05-29 / 2026-06-06

Related slices

PageWhat it containsOpen
Company jobsActive postings from Plus 2.Open
Company breakdownsRole, location, ATS, and work model facets for this company.Open
ATS provider jobsActive postings observed through Lever.Open
Provider filtered searchThe same provider as a filtered job collection.Open
City jobsActive postings in Santa Clara.Open
Department jobsActive postings in US Engineering.Open
Work model jobsActive Hybrid 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

CompanyPlus 2
Source94fb28bd-eddc-40df-9d19-0ed71e5a973b
ATS providerLever

Description

PlusAI is a Physical AI company pioneering AI-based virtual driver software for factory-built autonomous trucks. Headquartered in Silicon Valley with operations in the United States and Europe, Plus was named by Fast Company as one of the World’s Most Innovative Companies. Partners including TRATON GROUP’s Scania, MAN, and International brands, Hyundai Motor Company, Iveco Group, Bosch, and DSV are working with Plus to accelerate the deployment of next-generation autonomous trucks. If you’re ready to make a huge impact and drive the future of autonomy, Plus is looking for talented individuals to join its fast-growing teams. We are seeking a Senior Machine Learning Engineer with expertise in deep learning and data analysis. In this role, you will apply data-driven techniques to develop high-fidelity, scalable vehicle simulation models tailored to various vehicle platforms. You will collaborate with cross-functional teams to advance autonomous driving technology and drive innovation in simulation and model development. Your opportunities joining PlusAI Work, learn and grow in a highly future-oriented, innovative and dynamic field. Wide range of opportunities for personal and professional development. Catered free lunch, unlimited snacks and beverages. Highly competitive salary and benefits package, including 401(k) plan. Responsibilities: Develop accurate, scalable vehicle dynamics models from collected road test data, leveraging deep learning and advanced data analysis techniques. Conduct in-depth analysis of road test data to identify trends, anomalies, and key performance indicators to enhance model accuracy. Integrate the data-driven models into simulation pipelines with seamless compatibility. Design and implement an automated modeling pipeline for periodic model training, evaluation, and updates. Collaborate with cross-disciplinary teams to reproduce and resolve issues encountered during real-world road tests. Ensure that technical work meets customer requirements, regulatory standards, and company quality policies. Ensure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts. Required Skills: MS (with 3+ years of relevant experience) or PhD new grad in mechanical, electrical, aerospace engineering, physics, computer science, or a related field. Extensive experience applying deep learning techniques to time series forecasting and data analysis. Proficient in Python with experience working in large codebases. Excellent communication skills and the ability to collaborate effectively in a team setting. Familiarity with state-of-the-art deep learning models and their applications. Ensure that technical work meets customer requirements, regulatory standards, and company quality policies. Preferred Skills Proficient in C++ Background in autonomous vehicle prediction, planning, and control Strong understanding of conventional vehicle dynamics modeling Experience with autonomous vehicle or robotics simulation and related concepts

Full job record

Job IDa48790115a90e696a8f480d33a7c090a925701ef
Org IDdc239754-39c5-4206-bef0-5ecf8b881a2f
Source ID94fb28bd-eddc-40df-9d19-0ed71e5a973b
Board ID94fb28bd-eddc-40df-9d19-0ed71e5a973b
Providerlever
Provider Job Keyf4fc6b45-6c2d-4d09-aece-fd046eb4b81b
TitleSenior Machine Learning Engineer, Simulation
Normalized Title
Statusactive
Activeyes
Location TextSanta Clara, CA
DepartmentUS Engineering
TeamSimulation
Employment TypeFull-time
Workplace Typehybrid
Remote Policyhybrid
CountryUnited States
RegionCA
CitySanta Clara
Salary RawUSD 130000-200000 per-year-salary
Salary Min130,000
Salary Max200,000
Salary CurrencyUSD
Salary Periodyear
Source URLhttps://jobs.lever.co/plus-2/f4fc6b45-6c2d-4d09-aece-fd046eb4b81b
Apply URLhttps://jobs.lever.co/plus-2/f4fc6b45-6c2d-4d09-aece-fd046eb4b81b/apply
First Seen At2026-05-29 06:58:18Z
Last Seen At2026-06-06 07:56:17Z
Last Checked At2026-06-06 07:56:17Z
Last Changed At2026-05-29 06:58:18Z
Inactive At
Source Posted At2024-11-27 17:49:32Z
Source Updated At
Raw Payload Uris3://job-postings-prod-raw-590183727216/raw/provider=lever/board=plus-2/date=2026-06-06/2026-06-06T07-56-16-851Z-c4bdb7ed5c0562a2423bc139989d32fb82dd58c6225e665375e8820bad53720f.json
Event Fields
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  "active_status": "active"
}
Parsed Structured
{
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  "location": {
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    "city": "Santa Clara",
    "region": "CA",
    "country": "United States",
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  "inferred_at": "2026-06-06T07:56:17.753Z",
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}
Extensions
{}
Native Structured
{
  "lists": [
    {
      "text": "Responsibilities:",
      "content": "\n<li>Develop accurate, scalable vehicle dynamics models from collected road test data, leveraging deep learning and advanced data analysis techniques.</li>\n<li>Conduct in-depth analysis of road test data to identify trends, anomalies, and key performance indicators to enhance model accuracy.</li>\n<li>Integrate the data-driven models into simulation pipelines with seamless compatibility.</li>\n<li>Design and implement an automated modeling pipeline for periodic model training, evaluation, and updates.</li>\n<li>Collaborate with cross-disciplinary teams to reproduce and resolve issues encountered during real-world road tests.</li>\n<li>Ensure that technical work meets customer requirements, regulatory standards, and company quality policies.</li>\n<li>Ensure that your work is performed in accordance with the company’s Quality Management System (QMS) requirements and contribute to continuous improvement efforts.</li>\n"
    },
    {
      "text": "Required Skills:",
      "content": "\n<li>MS (with 3+ years of relevant experience) or PhD new grad in mechanical, electrical, aerospace engineering, physics, computer science, or a related field.</li>\n<li>Extensive experience applying deep learning techniques to time series forecasting and data analysis.</li>\n<li>Proficient in Python with experience working in large codebases.</li>\n<li>Excellent communication skills and the ability to collaborate effectively in a team setting.</li>\n<li>Familiarity with state-of-the-art deep learning models and their applications.</li>\n<li>Ensure that technical work meets customer requirements, regulatory standards, and company quality policies.</li>\n"
    },
    {
      "text": "Preferred Skills",
      "content": "\n<li>Proficient in C++</li>\n<li>Background in autonomous vehicle prediction, planning, and control</li>\n<li>Strong understanding of conventional vehicle dynamics modeling</li>\n<li>Experience with autonomous vehicle or robotics simulation and related concepts</li>\n\n<div>&nbsp;</div>"
    }
  ],
  "country": "US",
  "createdAt": 1732729772744,
  "updatedAt": null,
  "categories": {
    "team": "Simulation",
    "location": "Santa Clara, CA",
    "commitment": "Full-time",
    "department": "US Engineering",
    "allLocations": [
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  },
  "salaryRange": {
    "max": 200000,
    "min": 130000,
    "currency": "USD",
    "interval": "per-year-salary"
  },
  "workplaceType": "hybrid"
}
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