Full-Time
Software Engineer
Release & Engineering Efficiency
Confirmed live in the last 24 hours
Anyscale
501-1,000 employees
Platform for scaling AI workloads
No salary listed
Junior, Mid
Bengaluru, Karnataka, India
- At least 2 year 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
- 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
- Experience working on programming languages, security, or cloud developer productivity tools is a plus
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 businesses that are integrating AI and ML into their operations, including major tech companies like OpenAI and Ant Group. Unlike many competitors, Anyscale focuses on providing a comprehensive solution that simplifies the scaling of complex AI workloads. The company's goal is to empower organizations to effectively utilize AI technologies by offering a reliable and efficient platform.
Company Size
501-1,000
Company Stage
Series C
Total Funding
$259.6M
Headquarters
San Francisco, California
Founded
2019
Simplify's Take
What believers are saying
- 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.
What critics are saying
- 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.
What makes Anyscale unique
- 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.
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Benefits
Medical, Dental, and Vision insurance
401K retirement savings
Flexible time off
FSA and Commuter benefits
Parental and family leave
Office & phone plan reimbursement
Growth & Insights and Company News
6 month growth
↑ 31%1 year growth
↓ -2%2 year growth
↑ 0%This partnership allows organizations to effectively manage and scale their ML workflows by integrating Astronomer's workflow management capabilities with Anyscale's distributed computing power.
Anyscale unveils new products and AI Platform enhancements at Ray Summit 2024.
SAN FRANCISCO, July 31, 2024 (GLOBE NEWSWIRE) - Anyscale, the company behind Ray, the open source framework for scalable AI, named industry veteran Keerti Melkote as chief executive officer following a year of 4x revenue growth and explosive open source adoption.
Anyscale and deepsense.ai develop a scalable cross-modal image retrieval system for e-commerce.
Join us in Atlanta on April 10th and explore the landscape of security workforce. We will explore the vision, benefits, and use cases of AI for security teams. Request an invite here. Thousands of companies use the Ray framework to scale and run highly complex, compute-intensive AI workloads — in fact, you’d be hard-pressed to find a large language model (LLM) that hasn’t been built on Ray. Those workloads contain loads of sensitive data, which, researchers have found, could be highly exposed through a critical vulnerability (CVE) in the open-source unified compute framework. For the last seven months, this flaw has allowed attackers to exploit thousands of companies’ AI production workloads, computing power, credentials, passwords, keys, tokens and “a trove” of other sensitive information, according to new research from Oligo Security. The vulnerability is under dispute — meaning that it is not considered a risk and has no patch. This makes it a “shadow vulnerability,” or one that doesn’t appear in scans. Fittingly, researchers have dubbed it “ShadowRay.”