Anyscale commercializes Ray, a popular open-source project for scalable machine learning, making distributed computing accessible to developers.

Anyscale, backed by prominent investors with $250+ million in funding, is seeking a Technical Curriculum Developer to shape the future of distributed computing education. This role combines technical expertise in machine learning with educational content development, focusing on Ray and the Anyscale AI Platform.

The position requires a unique blend of technical prowess and educational expertise, with a minimum of 5 years of experience in Machine Learning and cloud computing technologies. You'll be responsible for creating comprehensive learning experiences that empower developers and data scientists to leverage Ray's capabilities effectively.

As a Technical Curriculum Developer, you'll manage learning tools and platforms, design technical curricula for ML Engineers and AI Engineers, and translate complex technical concepts into accessible learning content. The role demands proficiency in Python programming and hands-on experience with data science libraries like XGBoost and TensorFlow.

The company offers an attractive compensation package including stock options, comprehensive healthcare coverage, 401k, education stipends, and various other benefits. Working in a hybrid environment, you'll collaborate with technical experts to create innovative training content that drives the adoption of Ray and Anyscale's platform.

This is an excellent opportunity for someone passionate about both technology and education, wanting to impact how developers learn and implement distributed computing solutions. You'll be at the forefront of AI infrastructure education, helping shape how the next generation of developers harness scalable computing power.

Technical Curriculum Developer position at Anyscale, focusing on creating educational content for Ray and AI platform users.

Technical Curriculum Developer

Anyscale commercializes Ray, a popular open-source project creating an ecosystem of libraries for scalable machine learning.

Anyscale, backed by prominent investors with $250+ million in funding, is revolutionizing distributed computing through Ray, their open-source project. As a Technical Services Engineer, you'll be at the forefront of helping customers implement and succeed with their ML/AI initiatives. The role combines technical expertise in ML/AI, customer advocacy, and problem-solving skills.

The position requires working from the San Francisco office three days a week (Mon, Tue, Thur) in a hybrid setup. You'll be responsible for being the technical advisor for key customers, managing their onboarding and adoption of the Anyscale platform. The role involves end-to-end ownership of customer issues, from troubleshooting to resolution, while participating in a follow-the-sun support model.

The ideal candidate brings 5+ years of customer-facing technical experience, with at least 2 years in a fast-paced startup environment. Strong knowledge of ML/AI, data engineering, and cloud platforms is essential. You'll work with industry leaders like OpenAI, Uber, Spotify, and Instacart who use Ray in their tech stacks.

This role offers competitive compensation ($119,360 - $186,857) plus comprehensive benefits including stock options, healthcare coverage, 401k, wellness and education stipends, and more. It's an opportunity to impact the future of distributed computing and AI while working with cutting-edge technology and prominent customers.

The position requires excellent communication skills, strong technical capabilities, and the ability to manage multiple customer needs simultaneously. You'll collaborate with product and engineering teams to improve the platform while building strong relationships with technical stakeholders. Experience with Ray, MLOps platforms, and LLMs is a plus.

Technical Services Engineer role at Anyscale, focusing on customer success with ML/AI platform implementation and support.

Technical Services Engineer

Anyscale commercializes Ray, an open-source project creating an ecosystem of libraries for scalable machine learning, making distributed computing accessible to developers.

Anyscale, backed by Andreessen Horowitz, NEA, and Addition with $250+ million in funding, is revolutionizing distributed computing through Ray, their open-source project. They're seeking a Software Engineer for their Ray Data team to work on the Datasets library and data processing capabilities. The role involves developing and maintaining Ray Datasets, which powers critical production use cases at companies like Amazon and Alibaba. You'll work with Apache Arrow and Ray Core, focusing on performance optimization, ML training integration, and stability improvements. The position offers competitive compensation ($170,112-$237,000) and comprehensive benefits. The ideal candidate should have experience with distributed systems and data processing technologies. This is an opportunity to impact how developers and data scientists scale ML applications from laptop to cluster.

Software Engineer position at Anyscale focusing on Ray Data, building and optimizing distributed data processing capabilities for machine learning applications.

Software Engineer (Ray Data)

AI and distributed computing platform company specializing in Ray framework and LLM infrastructure

Anyscale is seeking a Research Engineer specializing in Large Language Models (LLMs) to join their team. The role will focus on advancing the company's AI capabilities and working with distributed computing systems. As part of the AI team, you'll be working on cutting-edge LLM research and development, helping to scale and optimize AI models using Ray framework. This position offers the opportunity to work at the intersection of distributed systems and artificial intelligence, contributing to the development of next-generation AI infrastructure. The role combines practical engineering with research aspects, making it ideal for someone passionate about both implementing and innovating in the AI space. You'll be working from our San Francisco office in a hybrid setting, collaborating with a team of experts in distributed computing and AI. This position represents an opportunity to shape the future of AI infrastructure and make significant contributions to the field of large language models.

Research Engineer position focused on Large Language Models (LLMs) at Anyscale, combining AI research with distributed systems engineering.

Research Engineer, LLM

Anyscale, backed by Andreessen Horowitz, NEA, and Addition with $250+ million in funding, is revolutionizing distributed computing through Ray, their open-source project. As a Deep Learning Performance Engineer, you'll be at the forefront of optimizing cutting-edge ML models, working with companies like OpenAI, Uber, and Spotify. This role is crucial for maintaining Anyscale's market-leading performance in AI infrastructure.

The position demands expertise in GPU/CUDA programming, deep learning frameworks, and system optimizations. You'll collaborate with product and research teams, implementing state-of-the-art practices in LLM engines. The role offers exciting opportunities to work with advanced technologies like vLLM and TensorRT-LLM.

The company provides comprehensive benefits including competitive equity, healthcare coverage, and various stipends for wellness and education. Located in San Francisco, you'll join a team dedicated to democratizing distributed computing and making it accessible to developers of all skill levels. This is an excellent opportunity for those passionate about performance engineering in AI and distributed systems.

Additional valued skills include ML Systems knowledge, experience with deep learning model training, and contributions to frameworks like PyTorch or TensorFlow. Experience with Ray or deep learning compilers would be advantageous. The role offers competitive compensation ranging from $170,112 to $237,000, reflecting Anyscale's data-driven and transparent approach to compensation.

Senior Deep Learning Performance Engineer role at Anyscale, focusing on optimizing ML models and building high-performance AI infrastructure systems.

Deep Learning Performance Engineer

Anyscale is commercializing Ray, a popular open-source project for scalable machine learning, democratizing distributed computing for software developers.

At Anyscale, we're building the best place to run Ray, democratizing distributed computing for software developers of all skill levels. We're seeking a Senior Full-Stack Software Engineer to join our Foundation Team, focusing on Enterprise Governance and Security. In this role, you'll shape the future of AI governance by building enterprise-grade tools for security, observability, and integrations at scale. You'll work on projects such as developing secure access and permissions systems, cost and usage optimization, and ensuring high levels of observability and automation within AI and ML-driven applications. We're looking for candidates with 5+ years of full-stack software engineering experience, expertise in SSO, RBAC, IAM, and permission systems, and familiarity with cost tracking and billing systems. Anyscale offers competitive compensation, including stock options, comprehensive healthcare, 401k, wellness and education stipends, paid parental leave, and flexible time off. Join us in transforming how enterprises leverage AI responsibly and efficiently.

Senior Full-Stack Software Engineer for Enterprise Governance and Security at Anyscale, building AI governance tools and secure systems.

Software Engineer, Enterprise Governance (Full-Stack)

Anyscale is on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We're commercializing Ray, a popular open-source project creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI, Uber, Spotify, Instacart, and Cruise use Ray in their tech stacks to accelerate AI applications.

As a Consulting Engineer at Anyscale, you'll be a core member of the team, contributing to customer implementations across the ML Ops lifecycle. Your responsibilities will include technical architecture assessment, model design and testing, deployment architectures, integration, debugging, and production operations. You'll also deliver classroom-based training, work with cross-functional teams, and influence the product roadmap.

The ideal candidate has:
- BS, MS, or PhD in Computer Science or related fields (or equivalent experience)
- 5+ years of hands-on experience delivering services to customers
- Excellent knowledge of Machine Learning and Deep Learning architectures and frameworks
- Experience with Python, MLOps, DevOps, virtualization, Docker, and Kubernetes in cloud environments
- Strong presentation, communication, and collaboration skills

Anyscale offers competitive compensation and benefits, including:
- Salary range: $222,010 - $275,057 per year
- Stock Options
- Comprehensive healthcare plans (99% covered for employees and dependents)
- 401k Retirement Plan
- Wellness and Education stipends
- Paid Parental Leave and Time Off
- Commute reimbursement
- In-office meals covered

Join Anyscale and be part of a team that's shaping the future of distributed computing and AI applications!

Join Anyscale as a Consulting Engineer to democratize distributed computing and advance AI applications using Ray.

Consulting Engineer

Anyscale is on a mission to democratize distributed computing and make it accessible to software developers of all skill levels, commercializing Ray, a popular open-source project for scalable machine learning.

Anyscale, backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised, is seeking exceptional AI/ML Engineers to join their hybrid research and product development team. In this role, you will collaborate with cross-functional teams to expand the usability of open source LLMs within Anyscale's ecosystem for enterprise applications. You'll experiment with models, build features for fine-tuning and inference, and work directly with customers to push the boundaries of their LLM use cases on Anyscale's AI platform.

Key responsibilities include:
- Designing, developing, and deploying cutting-edge AI/ML solutions for enterprise applications
- Contributing to features for fine-tuning and inference of LLMs
- Collaborating with customers to understand their needs and help them grow their use cases
- Conducting experiments to push the practical boundaries of open source LLMs
- Improving the performance, scalability, and usability of the AI platform
- Creating technical documentation and case studies

Qualifications:
- Master's degree with 3+ years of experience, or Ph.D. in a relevant field
- Strong technical skills in LLM architecture, training, and inference
- Hands-on experience with LLM training, fine-tuning, or inference optimization
- Experience with observability, monitoring, and debugging LLM systems
- Excellent technical writing skills
- Proactive, self-driven, and adaptable to a startup environment

Anyscale offers competitive compensation, including a salary range of $170,112 ~ $237,000, stock options, comprehensive healthcare plans, 401k, wellness and education stipends, paid parental leave, flexible time off, and more. The company is based in San Francisco, CA, with employees required to come to the office 3 times a week.

Join Anyscale and be part of a team that's making distributed computing and AI accessible to developers worldwide!

AI/ML Engineer role at Anyscale, focusing on expanding open source LLM usability for enterprise applications.

AI/ML Engineer - Large Language Models

Anyscale is on a mission to democratize distributed computing and make it accessible to software developers of all skill levels by commercializing Ray, a popular open-source project for scalable machine learning.

Anyscale is seeking talented engineers to join their team and contribute to the development of next-generation, high-performance machine learning serving systems. The Platform team is dedicated to creating world-class systems for serving ML models in production, including building and maintaining the open-source Ray Serve library and contributing directly to the Anyscale platform.

As part of this role, you will:
- Develop a highly available service for ML model serving
- Enhance Ray Serve and other libraries to simplify the development of next-generation ML applications in production
- Improve autoscaling capabilities to drive performance enhancements and cost savings
- Optimize latency and throughput for both single- and multi-model serving scenarios

Requirements:
- Solid background in algorithms, data structures, and system design
- Experience working with modern machine learning tooling, including PyTorch, TensorFlow, and JAX
- At least 2+ years of relevant work experience

Bonus points for:
- 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 offers competitive compensation and benefits, including:
- Target salary range: $170,112 ~ $237,000
- Stock Options
- Healthcare plans (99% premiums covered)
- 401k Retirement Plan
- Wellness and Education stipends
- Paid Parental Leave
- Flexible Time Off
- Commute reimbursement
- 100% of in-office meals covered

Anyscale is based in San Francisco, CA, with employees required to come to the office 3x a week. The company values diversity and inclusion and encourages individuals from underrepresented groups to apply.

Join Anyscale as a Software Engineer (ML Platform) to develop high-performance machine learning serving systems and contribute to Ray Serve.

Software Engineer (ML Platform)

Anyscale is commercializing Ray, a popular open-source project creating an ecosystem of libraries for scalable machine learning.

Anyscale is on a mission to democratize distributed computing and make it accessible to software developers of all skill levels. We're commercializing Ray, a popular open-source project that's creating an ecosystem of libraries for scalable machine learning. Companies like OpenAI, Uber, Spotify, Instacart, Cruise, and many more use Ray in their tech stacks to accelerate AI applications.

We're building the best place to run Ray, allowing any developer or data scientist to scale an ML application from their laptop to the cluster without needing to be a distributed systems expert. Backed by Andreessen Horowitz, NEA, and Addition, we've raised over $250 million to date.

As a Staff Software Engineer / Tech Lead Manager at Anyscale, you'll work on challenging architectural problems, develop high-quality software to empower developers, and collaborate with leading experts in distributed systems and machine learning. We're looking for candidates who can help lay down solid architectural foundations for the future of Ray and Anyscale.

Key Responsibilities:
- Develop high-quality software for the Anyscale platform
- Tackle difficult architectural problems
- Work closely with end users to iterate on the product
- Communicate your work through talks, tutorials, and blog posts
- Help build and shape a world-class company

Requirements:
- 5+ years of building, scaling, and maintaining software systems in production environments
- Solid fundamentals in algorithms, data structures, and system design
- Experience designing fault-tolerant distributed systems
- Strong architectural skills

Bonus Points:
- Experience with cloud technology stacks (AWS, GCP, Kubernetes)
- Experience building ML training pipelines or inference services in production
- Experience with big data tools (Spark, Flink, Hadoop)
- Experience managing small teams pursuing ambitious technical goals

We offer competitive compensation, stock options, and comprehensive benefits, including healthcare plans, 401k, wellness and education stipends, paid parental leave, flexible time off, and more. Join us in building the future of software development!

Join Anyscale as a Staff Software Engineer / Tech Lead Manager to build the future of distributed computing and scalable machine learning.

Anyscale Engineering Jobs

Anyscale commercializes Ray, a popular open-source project for scalable machine learning, making distributed computing accessible to developers.