Research Engineer, Magic

• Strong general software engineering skills
• Thorough knowledge of the deep learning literature
• Experience with pre- and post-training of LLMs
• Ability to come up with and evaluate research ideas
• Experience working with large distributed systems
• Ability to handle large ETL workloads

• As a research engineer, you’ll work on training, evaluating, and serving large AI models and new inference-time compute techniques, build internet-scale datasets, and help prototype new research and product ideas
• Optimize inference throughput for novel model architectures
• Contribute to frameworks used for our research and production workloads
• Train trillion-parameter models on large GPU clusters
• Curate post-training datasets to improve targeted capabilities
• Build out internet-scale data pipelines and crawlers
• Design, prototype and optimize new model architectures
• Contribute to research across long-context, inference-time compute, RL, and more

• Equity: Significant equity compensation
• Retirement savings: 401K with 6% salary matching
• Healthcare: Health, dental and vision insurance for you and your dependents
• Time off: Unlimited paid time off to support balance in your work and life
• Office catering: Chef-prepared lunch and dinner
• Wellbeing: Access to mental health, financial wellbeing, and telehealth programs

Total funding: $465m

Magic is a startup that uses AI to help with coding. It supplies a set of tools that can write and manage code for software projects, almost like having a smart assistant that understands programming. Interestingly, its technology can handle large amounts of code and remember details over long stretches of work.