Senior Software engineer- Reliability

Job Description

This job posting has expired and no longer accepting applications.

Luma’s mission is to build multimodal AI to expand human imagination and capabilities.

We believe that multimodality is critical for intelligence. To go beyond language models and build more aware, capable and useful systems, the next step function change will come from vision. So, we are working on training and scaling up multimodal foundation models for systems that can see and understand, show and explain, and eventually interact with our world to effect change.

The SRE role at Luma AI sits in the infrastructure team, and is responsible for defining, measuring, and improving the reliability of Luma’s GPU clusters. The SRE team works closely with the research teams to improve the functioning of the existing research platform and build the future platform.This is the team that helps make the infrastructure enabling progress at the leading AI lab.

In addition to cash base pay, you'll also receive a sizable grant of Luma's equity.

The pay range for this position is for Bay Area. Base pay offered may vary depending on job-related knowledge, skills, candidate location, and experience.

Startup Mindset

Value velocity and execution.

Communicate clearly.

Focus on building what will matter to users and the product.

Be resourceful at finding creative ways to overcome challenges.

Experience

Proven work experience 5+ yrs as an reliability engineer, production engineer, infrastructure software engineer or a similar role in a fast-paced, rapidly scaling company.

Strong proficiency in GPU cloud infrastructure, including the underlying concepts of scheduling, scaling, cloud storage, networking and security.

Proficiency in programming/scripting languages.

Experience with containerization technologies and container orchestration platforms like Kubernetes or equivalent.

Knowledge of IaC tools such as Terraform or CloudFormation or equivalent.

Excellent problem-solving and troubleshooting skills.

Strong communication and collaboration skills.

Experience with observability tools; examples include DataDog, Prometheus, Grafana, Splunk and ELK stack or similar.

Knowledge of security best practices in cloud environments.

Good to have experience as an SRE within the AI/ML space is strongly preferred.