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Machine Learning Engineer, Driving Foundation Models

Sunnyvale, United States · San Francisco, Califonia, US

Pay
$175,000–250,000/yearAnnual period assumed — pay source
Compensation $175,000 - $250,000 Additional Information
Read the full posting
Work setting
Not stated
Employment
Full-time — employment source
Employment type: Full-time
From the employer’s posting
Team
ENGINEERING › Autonomous Driving (AD) — team source
Department: ENGINEERING › Autonomous Driving (AD)
From the employer’s posting

Before you apply

Sponsorship
Visa sponsorship not confirmed — sponsorship source
2. Do you now, or will you in the future, require immigration sponsorship for work authorization (for example, H-1B status)?
From the employer’s application form
Apply at 42dot

What you’ll work on

Full posting

Develop driving and physical AI foundation models.

Tools in this posting

  • C++
  • Go
  • Python
  • AWS
  • Azure
  • Docker
  • Kubernetes
  • Hugging Face
  • PyTorch
  • TensorFlow
  • GCP
Source — Tool mentions in context
Qualifications - Languages: Python, C++, and Golang (for high-throughput systems). - Frameworks: PyTorch, JAX, Hugging Face ecosystem, vLLM.
- Frameworks: PyTorch, JAX, Hugging Face ecosystem, vLLM. - Infrastructure: Kubernetes, Docker, multi-node distributed training (Megatron-LM, DeepSpeed), and cloud platforms (AWS, Azure, Google Cloud). - Math & Theory: Linear algebra, calculus, probability, statistics, and deep learning architectures (Transformers, diffusion models).
- Languages: Python, C++, and Golang (for high-throughput systems). - Frameworks: PyTorch, JAX, Hugging Face ecosystem, vLLM. - Infrastructure: Kubernetes, Docker, multi-node distributed training (Megatron-LM, DeepSpeed), and cloud platforms (AWS, Azure, Google Cloud).
- Data Curation & Pretraining: Design and manage massive, multi-terabyte datasets, including data scraping, filtering, deduplication, tokenization, and synthetic data generation. - Distributed Model Training: Scale training across massive GPU/TPU clusters using parallel processing, custom data loaders, and framework optimization (PyTorch, JAX, or TensorFlow). - Post-Training & Alignment: Implement instruction tuning, Reinforcement Learning from Human Feedback (RLHF), or direct preference optimization to align models with safety and behavior goals.

About 42dot

42dot is a mobility AI company committed to solving mobility challenges with software and AI.

In the employer’s words · Read in context · Company website ↗

Posting record

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Live
First seen by us
Oct 28, 2026 · today
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Job description

View original posting ↗

We are looking for the best

About Us

42dot is a mobility AI company committed to solving mobility challenges with software and AI. As the Global Software Center of Hyundai Motor Group, 42dot pioneers the future of mobility by advancing the development of software-defined vehicles. 

We develop safety-first, user-centric software-defined vehicle technologies that deliver the latest performance through continuous updates like smartphones. By advancing software and AI technology, 42dot envisions a world where everything is connected and moves autonomously through a self-managing urban transportation operating system.

About the Role

Develop driving and physical AI foundation models. Support Aria VLA model development.

Responsibilities

  • Data Curation & Pretraining: Design and manage massive, multi-terabyte datasets, including data scraping, filtering, deduplication, tokenization, and synthetic data generation.

  • Distributed Model Training: Scale training across massive GPU/TPU clusters using parallel processing, custom data loaders, and framework optimization (PyTorch, JAX, or TensorFlow).

  • Post-Training & Alignment: Implement instruction tuning, Reinforcement Learning from Human Feedback (RLHF), or direct preference optimization to align models with safety and behavior goals.

  • Inference & Optimization: Compress and optimize models (quantization, pruning, speculative decoding) to run at low latency on cloud infrastructure or edge hardware like smartphones and robotics.

  • Evaluation & Guardrails: Build benchmarking harnesses, hallucination checkers, and red-teaming pipelines to test model accuracy and safety.

Qualifications

  • Languages: Python, C++, and Golang (for high-throughput systems).

  • Frameworks: PyTorch, JAX, Hugging Face ecosystem, vLLM.

  • Infrastructure: Kubernetes, Docker, multi-node distributed training (Megatron-LM, DeepSpeed), and cloud platforms (AWS, Azure, Google Cloud).

  • Math & Theory: Linear algebra, calculus, probability, statistics, and deep learning architectures (Transformers, diffusion models).

Interview Process

  • Application Review - Coding Test - 1st interview - 2nd interview - Offer Negotiation - Hiring

  • The screening procedures may vary depending on the position, schedule, or other circumstances.

    You will be individually notified of the screening schedule and results via the email address provided in your application.

Compensation

  • $175,000 - $250,000

Additional Information

  • In accordance with fair hiring practices, do not include any personal information unrelated to your job qualifications (e.g., Social Security Number, family relations, marital status, age, photo, physical condition, place of birth, etc.) in your resume.

  • All documents must be submitted in PDF format and under 30MB in size.

  • If you experience issues uploading your resume, please send it along with the job posting URL to recruit@42dot.ai.

  • We strongly encourage applications from U.S. veterans and candidates eligible for employment preference under applicable laws.

  • Qualified individuals with disabilities are encouraged to apply and will receive consideration under the Americans with Disabilities Act (ADA).

  • 42dot does not accept unsolicited resumes and will not pay fees for any such submissions. Equal Opportunity Statement

  • 42dot is an Equal Opportunity Employer. We celebrate diversity and are committed to creating an inclusive environment for all employees, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, or veteran status.

※ Please review the following information before applying.

Source details

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Pay
Compensation $175,000 - $250,000 Additional Information
Location & working pattern

San Francisco, Califonia, US

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