
Posted 12 days ago
Machine Learning Engineer, Driving Foundation Models
AI Summary
This role develops driving and physical AI foundation models, covering large-scale data curation, distributed GPU training, post-training alignment, model optimization for low-latency inference, and safety evaluation. It supports the Aria VLA model development effort.
About this role
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 .
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.
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