Magic AI
Software Engineer - Supercomputing Platform
Magic AI, San Francisco, California, United States, 94199
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 test-time compute to achieve this goal.
About the role:
As a Software Engineer on our Supercomputing Platform & Infrastructure team, you will design and build resilient and optimized solutions for AI workloads on massive Computing Clusters.
What you might work on:
Build the software stack to run massive-scale (thousands of GPUs), highly available and secure AI training and inference infrastructure
Troubleshoot and resolve complex issues across GPU resources, networking, OS, drivers and cloud environments, and automate detection and recovery processes
Ensure reliability and availability of GPU workloads for training and production inference
Investigate and resolve incidents across security and availability
Develop platform engineering solutions to enhance the efficiency and speed of our engineers
Proactively explore ways to accelerate Magic’s research and engineering teams
What we’re looking for: Experience working with production GPU deployments
Strong understanding of networking technologies
Extensive experience with GCP, AWS, Azure or similar cloud platforms
Strong software engineering skills
Strong IaC knowledge with extensive experience in Terraform or Pulumi
Magic strives to be the place where high-potential individuals can do their best work. We value quick learning and grit just as much as skill and experience. 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
Compensation, benefits and perks (US): Annual salary range: $100K - $1M
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 dependants
Unlimited paid time off
Option to work in-person in SF or remotely
Visa sponsorship and relocation stipend to bring you to SF
A small, fast-paced, highly focused team
#J-18808-Ljbffr
Troubleshoot and resolve complex issues across GPU resources, networking, OS, drivers and cloud environments, and automate detection and recovery processes
Ensure reliability and availability of GPU workloads for training and production inference
Investigate and resolve incidents across security and availability
Develop platform engineering solutions to enhance the efficiency and speed of our engineers
Proactively explore ways to accelerate Magic’s research and engineering teams
What we’re looking for: Experience working with production GPU deployments
Strong understanding of networking technologies
Extensive experience with GCP, AWS, Azure or similar cloud platforms
Strong software engineering skills
Strong IaC knowledge with extensive experience in Terraform or Pulumi
Magic strives to be the place where high-potential individuals can do their best work. We value quick learning and grit just as much as skill and experience. 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
Compensation, benefits and perks (US): Annual salary range: $100K - $1M
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 dependants
Unlimited paid time off
Option to work in-person in SF or remotely
Visa sponsorship and relocation stipend to bring you to SF
A small, fast-paced, highly focused team
#J-18808-Ljbffr