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Machine Learning Engineer
Voltai Com
Menlo ParkOn-site1y ago
- Employment
- Full-time
About the role
- 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 to support foundation model development
- Train, fine-tune, and deploy foundation models, optimizing for latency, accuracy, and cost across diverse deployment scenarios
- Design cutting-edge retrieval and search algorithms for use in engineering documentation, design 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 SOTA research into production-ready code, working 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
- 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.
- 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
- 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.
Perks & benefits
- Vision Insurance
- Medical Insurance
- Unlimited Vacation
- Paid Time Off
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