Research Engineer, Handshake

• Strong Python programming skills with attention to clean, efficient, and scalable code
• Experience building and operating large-scale systems for model post-training, specialized data processing, or benchmark evaluation
• Deep familiarity with PyTorch and modern post-training techniques (RLHF, constitutional AI, etc.)
• A background in applied machine learning, model evaluation, or large-scale data quality assessment
• Experience with benchmark design, evaluation methodologies, and performance measurement frameworks
• Clear communication skills and a collaborative mindset for cross-functional research teams

Desirable

• We're looking for a Research Engineer to join our Handshake AI Research team, where you'll help shape what the next generation of AI models can achieve. This is a hands-on, high-impact role focused on post-training methodologies, specialized domain data verification, and creating cutting-edge LLM benchmarks that measure real-world impact
• As a Research Engineer, you'll bring deep technical skill, curiosity, and rigor to every stage of the research-to-deployment pipeline—whether it's designing robust distributed infrastructure for massive experiments, writing high-performance ML code, or developing benchmarks and evaluations that define the future of AI capabilities
• Design and implement post-training systems and methodologies in close partnership with research scientists and domain experts
• Build and maintain infrastructure that supports large-scale model training, specialized data processing, and benchmark evaluation
• Develop robust frameworks for verifying the quality and integrity of highly specialized domain datasets
• Create next-generation LLM benchmarks that push the boundaries of model evaluation and capabilities assessment
• Optimize performance across software and hardware layers to accelerate post-training experimentation and deployment
• Collaborate across disciplines to ensure rigorous validation of model improvements and benchmark reliability