Handshake is seeking an AI Research Engineer to join their AI team, focusing on shaping the future of AI through advanced data solutions and model evaluation. The role combines deep technical expertise with practical implementation in a fast-growing environment.
The position offers a unique opportunity to work directly with top AI labs, leveraging Handshake's extensive network of 18 million students and 500K+ PhDs. As an AI Research Engineer, you'll be responsible for designing and implementing post-training systems, building robust infrastructure for model training, and developing cutting-edge LLM benchmarks.
The ideal candidate will bring strong Python programming skills, extensive experience with PyTorch, and deep knowledge of modern post-training techniques like RLHF and constitutional AI. You'll work in a collaborative environment with research scientists and domain experts, focusing on pushing the boundaries of AI capabilities through better data and evaluation methods.
Handshake offers a comprehensive benefits package including competitive salary ($180K-$300K), equity, extensive healthcare coverage, generous parental leave, and various stipends for professional development and workplace comfort. The company's unique position in the education and AI sectors, combined with its partnership with leading AI research labs, makes this an exceptional opportunity for someone passionate about advancing the field of artificial intelligence.
The role is based in San Francisco or New York, offering a collaborative in-person environment with modern facilities and regular team interactions. You'll be joining a world-class team assembled from companies like YC, Notion, Scale, Coinbase, and Palantir, working on projects that directly impact the future of AI development and evaluation.
This position is perfect for a senior engineer who wants to combine technical expertise with research innovation, working on problems that matter in the rapidly evolving field of artificial intelligence. The role offers both technical challenges and the opportunity to shape how AI models are built, tested, and evaluated at the industry's frontier.