Role: Machine Learning Engineer
Location: Menlo Park, CA
About our client:
Our client is a leading AI company building agentic systems and frontier foundation models for semiconductor and electronics design. Backed by top-tier investors, they are putting AI in the hands of hardware engineers in over 70% of the world’s largest semiconductor and electronics companies to provide effortless control over next-generation chip and board designs. Their work powers the future of automotive, industrial automation, consumer electronics, IoT, and semiconductor manufacturing.
Their founding team consists of IOI/IPhO olympiad medalists, Stanford professors, and the former CTO of a major EDA company. Their business leadership has scaled revenue in previous companies to over $1.5bn. They are bringing together world-class talent at the intersection of software and hardware.
Position Overview:
The Machine Learning Engineer will design, build, and optimize foundation models, retrieval pipelines, and agentic frameworks tailored to the semiconductor and electronics domain. This role requires deep expertise in large-scale AI systems, model training and fine-tuning, and the ability to translate cutting-edge research into production-ready solutions.
Key Responsibilities:
- Architect and develop high-performance AI systems that combine LLMs, retrieval pipelines, and agentic frameworks tailored to semiconductor and electronics design tasks.
- Curate, manage, and optimize large-scale training and evaluation datasets, leveraging both synthetic and human-collected data.
- Train, fine-tune, and deploy foundation models, optimizing for latency, accuracy, and cost across diverse deployment scenarios.
- Design advanced retrieval and search algorithms for engineering documentation, schematics, datasheets, and other technical corpora.
- Build robust evaluation pipelines to measure model performance across tasks such as code generation, schematic synthesis, and long-context reasoning.
- Translate state-of-the-art research into production-ready code across the full ML stack from paper to GPU.
- Own strategic technical initiatives, collaborating with customers, engineers, and researchers to solve domain-specific problems with measurable impact.
Qualifications:
- Strong programming expertise in Python, C, or Rust, with a focus on writing performant and maintainable code for large-scale AI systems.
- Proficiency in Python and PyTorch: Strong experience in developing and training models using PyTorch
- GPU Programming with CUDA: Hands-on experience optimizing model training and inference on GPUs using CUDA, including custom kernel development
- Distributed Computing Frameworks: Familiarity with tools like DeepSpeed, Accelerate, Unsloth, or Kubeflow for efficient large-scale model training
- Training and Fine-Tuning: Expertise in fine-tuning and quantizing transformer-based models
- Research to Production: Proven ability to translate academic research papers into scalable, production-ready code.
- Experience in AI Research and Development: Background in AI companies or research labs, contributing to significant machine learning projects.
- Understanding of Model Evaluation and Deployment: Experience in evaluating model performance, deploying models into production environments, and monitoring their performance post-deployment.
- Bonus Points:
- Some background in hardware/electronics, gained through professional, academic, or personal projects
- Contributions to open-source initiatives
- Notable awards or publications in leading journals/conferences
- Experience thriving in a fast-paced, hyper-growth startup environment
What they offer (compensation, benefits, etc.):
- Unlimited PTO: Recharge when you need it, no questions asked.
- Comprehensive Health Coverage: Medical, dental, and vision insurance for you and your dependents.
- Free Meals and Snacks: Daily lunches, dinners, and snacks in the office.
- Professional Growth: We invest in your continuous learning and offer opportunities to expand your skills.
- Visa Sponsorship: We welcome global talent and provide visa sponsorship to support qualified candidates.