AI Summary
As a Research Engineer at Magic, you will work on training, evaluating, and serving large AI models, building internet-scale datasets, and prototyping new research and product ideas. You will contribute to frameworks used for research and production workloads, optimize inference throughput for novel model architectures, and design and implement new model architectures.
Key Highlights
Training and serving large AI models
Building internet-scale datasets
Prototyping new research and product ideas
Technical Skills Required
Benefits & Perks
Annual salary range: $225K - $550K
Equity is a significant part of total compensation
401(k) plan with 6% salary matching
Generous health, dental and vision insurance
Unlimited paid time off
Visa sponsorship and relocation stipend
Job Description
Magic’s mission is to build safe AGI that accelerates humanity’s progress on the world’s most important problems. We believe the most promising path to safe AGI lies in automating research and code generation to improve models and solve alignment more reliably than humans can alone. Our approach combines frontier-scale pre-training, domain-specific RL, ultra-long context, and inference-time compute to achieve this goal.
About the role:
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.
What you might work on:
- 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
- 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
Our culture:
- Integrity. Words and actions should be aligned
- Hands-on. At Magic, everyone is building
- Teamwork. We move as one team, not N individuals
- Focus. Safely deploy AGI. Everything else is noise
- Quality. Magic should feel like magic
- Annual salary range: $225K - $550K
- Equity is a significant part of total compensation, in addition to salary
- 401(k) plan with 6% salary matching
- Generous health, dental and vision insurance for you and your dependents
- Unlimited paid time off
- Visa sponsorship and relocation stipend to bring you to SF, if possible
- A small, fast-paced, highly focused team