Software Engineer (Ray Core) at Anyscale

Bengaluru, Karnataka, India

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Not SpecifiedCompensation

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 relevant work experience
Solid background in algorithms, data structures, system design
Experience in building scalable and fault-tolerant distributed systems
Knowledge of distributed model training and inference (e.g., tensor parallel, pipeline parallel) is preferred
Knowledge of GPU programming is preferred

Responsibilities

Develop high quality open source software to simplify distributed programming (Ray)
Identify, implement, and evaluate architectural improvements to Ray core
Improve the testing process for Ray to make releases as smooth as possible
Communicate your work to a broader audience through talks, tutorials, and blog posts

Skills

Key technologies and capabilities for this role

C++Distributed SystemsSystems ProgrammingPerformance OptimizationFault ToleranceSchedulerMemory ManagementI/O SubsystemsStress TestingOpen Source

Questions & Answers

Common questions about this position

What experience level is required for the Software Engineer role on Ray Core?

At least 2 years of relevant work experience is required.

What key skills are needed for this position?

A solid background in algorithms, data structures, system design, and experience in building scalable and fault-tolerant distributed systems are required. Knowledge of distributed model training and inference, as well as GPU programming, is preferred.

Is this a remote position or does it require office work?

This information is not specified in the job description.

What is the salary or compensation for this role?

This information is not specified in the job description.

What does the Ray Core team work on?

The Ray Core team develops and maintains the Ray C++ backend, including the distributed scheduler, language runtime integration, I/O and memory subsystems, focusing on reliability, scalability, performance, and supporting higher-level libraries.

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.

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