Full-Time
Anyscale
501-1,000 employees
Platform for scaling AI workloads
Compensation Overview
$170.1k - $237k/yr
Junior, Mid
Palo Alto, CA, USA + 1 more
More locations: San Francisco, CA, USA
Hybrid position requiring in-office presence in either San Francisco or Palo Alto, CA.
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- A solid background in algorithms, data structures, and system design.
- Experience working with modern machine learning tooling, including PyTorch, TensorFlow, and JAX.
- At least 2+ year of relevant work experience.
- Develop a highly available service for ML model serving.
- Enhance Ray Serve and our other libraries to simplify the development of next-generation ML applications in production.
- Improve our autoscaling capabilities to drive performance enhancements and cost savings.
- Optimize latency and throughput for both single- and multi-model serving scenarios.
- Experience in building and maintaining open-source projects.
- Experience in building and operating machine learning infrastructure in production.
- Experience in building highly available serving systems.
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. Clients, such as OpenAI and Ant Group, utilize Ray to train large models and enhance the performance and reliability of their ML systems. Anyscale's platform has been reported to improve scalability, latency, and cost-efficiency by over 90% for some users. The company operates on a software-as-a-service (SaaS) model, allowing clients to subscribe for access to Ray and its features, ensuring a consistent revenue stream. Anyscale's goal is to empower organizations to efficiently scale their AI workloads and optimize their operations.
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
↑ 18%1 year growth
↓ -2%2 year growth
↓ -1%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.”