Machine Learning Research Scientist

About Voltai Voltai is the leading AI company building agentic systems and frontier foundation models for semiconductor and electronics design. Backed by Sequoia Capital, we’re putting AI in the hands of hardware engineers in over 70% of the world’s largest semiconductor and electronics companies to have effortless control over their next-generation chip and board designs, powering the future of automotive, industrial automation, consumer electronics, IoT, and semiconductor manufacturing. About the Team Our founding team consists of IOI/IPhO olympiad medalists, Stanford professors, ex-CTO of Synopsys, and our business leadership has scaled revenue in their previous companies to over $1.5bn. At Voltai, we are combining the world’s best talent in the intersection of software and hardware. Key Responsibilities Conduct original research in machine learning and AI with a focus on models that integrate multiple modalities. Develop, train, and fine-tune large language models (LLMs) and multi-modal models (MMMs). Explore and scale trillion-parameter neural networks, along with smaller, specialized models. Design and implement models capable of solving discrete and continuous constraint reasoning tasks and graph-related challenges. Develop and evaluate interconnected systems comprising LLMs, NLP models, and retrieval algorithms. Publish research findings in top AI conferences and journals, contributing to the academic and industry community. Collaborate with cross-functional teams to translate research outcomes into practical applications. Innovate and create data synthetically and collect it from human interactions for diverse tasks. Lead efforts in optimizing both open-source and proprietary models, considering various constraints. Required Skillsets Strong background in machine learning, including sequence modeling, generative models, and model architecture. Expertise in Pytorch, Python, CUDA, and Triton. Proven research experience with a strong publication record in top AI conferences and journals. Deep understanding of pre-training and fine-tuning large multi-modal models. Experience implementing research papers into production code. Familiarity with the latest state-of-the-art techniques, including prompting and inference-time search methods. Experience in developing and managing large-scale machine learning systems. Proficiency in configuring and optimizing hardware and operating systems for maximum performance. Experience building distributed training systems for AI models in high-performance computing (HPC) clusters. Our Benefits 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.