Machine Learning Engineer

About Voltai:Voltai is an AI company building frontier foundation models and agentic systems for semiconductor and electronics design.We are one of the fastest-growing startups (in terms of valuation and revenue bookings) and leader in AI for electronics design. Backed by the world's top VC firm, we are working with some of the world’s largest semiconductor and electronics companies.The founding team consists of Olympiad medalists, ICPC world champions, and university professors. In addition, our business team has a proven track record, having scaled revenue from $0 to $400M in just four years at their previous company.
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 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

Required Skill Sets:

• 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

Our Benefits:

• Unlimited PTO: We trust you to manage your time and know when you need a break. Recharge when you need it, no questions asked.
• Comprehensive Health Coverage: Your health matters. We offer top-tier medical and dental insurance to keep you and your loved ones covered.
• Commitment to Your Growth: At Voltai, we’re dedicated to your continuous learning and development. Whether it’s through challenging projects or opportunities for professional advancement, we invest in your journey to becoming a leader in your field.
• Visa Sponsorship: We support international talent and offer visa sponsorship to help you join our team, no matter where you are in the world.