Software Engineer, Release & Engineering Efficiency at Anyscale

San Francisco, California, United States

Apply Now

$172,500 – $240,000Compensation

Mid-level (3 to 4 years), Senior (5 to 8 years)Experience Level

Full TimeJob Type

UnknownVisa

Technology, AI, Machine LearningIndustries

Requirements

At least 2 years of software engineering experience in CI/CD, build systems (Bazel), large-scale systems engineering or distributed systems in a cloud environment
Experience with Infrastructure as Code tooling (Terraform, Cloudformation, Pulumi, etc)
Experience with AWS cloud infrastructure (EC2, S3, IAM, Docker, etc)
Experience with Kubernetes
Experience working on programming languages, security, or cloud developer productivity tools is a plus

Responsibilities

Design and implement developer velocity improvement projects across all engineering teams
Define and deliver developer-focused solutions CI/CD tools, build system, automated releases systems that enable scalable development
Design, build and maintain core testing infrastructure to ensure that Ray remains an industry-leading scalable and distributed programming runtime and that our proprietary platform remains highly stable and scalable
Work with infrastructure teams to influence, develop, and evaluate Anyscale cluster management features
Work with the open source Ray team to design and implement distributed testing frameworks and applications to help ensure correctness of the program across operating systems, architecture, and underlying environments

Skills

Ray

Distributed Systems

Machine Learning

CI/CD

Build Systems

Automated Releases

Testing Infrastructure

Anyscale

Platform for scaling AI workloads

About Anyscale

Anyscale provides a platform designed to scale and productionize artificial intelligence (AI) and machine learning (ML) workloads. Its main product, Ray, is an open-source framework that helps developers manage and scale AI applications across various fields, including Generative AI, Large Language Models (LLMs), and computer vision. Ray allows companies to enhance the performance, fault tolerance, and scalability of their AI systems, with some users reporting over 90% improvements in efficiency, latency, and cost-effectiveness. Anyscale primarily serves clients in the AI and ML sectors, including major companies like OpenAI and Ant Group, who rely on Ray for training large models. The company operates on a software-as-a-service (SaaS) model, charging clients a subscription fee for access to the Ray platform. Anyscale's goal is to empower organizations to effectively scale their AI workloads and optimize their operations.

San Francisco, CaliforniaHeadquarters

2019Year Founded

$252.5MTotal Funding

SERIES_CCompany Stage

Enterprise Software, AI & Machine LearningIndustries

201-500Employees

Benefits

Medical, Dental, and Vision insurance

401K retirement savings

Flexible time off

FSA and Commuter benefits

Parental and family leave

Office & phone plan reimbursement

Risks

ShadowRay vulnerability in Ray framework poses significant security risk with no patch.

OctoML's OctoAI service increases competition in AI infrastructure market.

Dependency on Nvidia's technology could be risky if Nvidia faces issues.

Differentiation

Anyscale's Ray framework scales AI applications from laptops to cloud seamlessly.

Ray is widely used in Generative AI, LLMs, and computer vision fields.

Anyscale's SaaS model provides recurring revenue through subscription fees for Ray platform.

Upsides

Anyscale's $100M Series C funding indicates strong investor confidence and growth potential.

Partnership with Nvidia enhances performance and cost-efficiency for AI deployments.

Anyscale Endpoints offers 10X cost-efficiency for popular open-source LLMs.

Land your dream remote job 3x faster with AI

Try Jobo Free