About Anyscale:
At Anyscale, we're 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, have Ray in their tech stacks to accelerate the progress of AI applications out into the real world.With Anyscale, we’re building the best place to run Ray, so that any developer or data scientist can scale an ML application from their laptop to the cluster without needing to be a distributed systems expert.Proud to be backed by Andreessen Horowitz, NEA, and Addition with $250+ million raised to date.
About the role
We are seeking exceptional AI/ML Engineers to join our hybrid research and product development team. In this role, you will collaborate closely with cross-functional teams to expand the usability of open source LLMs within Anyscale’s ecosystem for enterprise applications. You will have the opportunity to experiment directly with models, build features for fine-tuning and inference, and work hand-in-hand with customers to push the boundaries of their LLM use cases on our AI platform.
As part of this role, you will
- Design, develop, and deploy cutting-edge AI/ML solutions for enterprise applications, making it easy and self-sufficient for customers to adopt AI in their applications
- Contribute to the development of features and enhancements for fine-tuning and inference of LLMs, ensuring a clear value proposition, elegant API design, and intuitive user experience
- Collaborate with customers to understand their needs, help them grow their use cases on our platform, and enable them to achieve their desired outcomes
- Conduct experiments and research to push the practical boundaries of open source LLMs within Anyscale’s ecosystem
- Continuously improve the performance, scalability, and usability of our AI platform, adopting a full-stack approach to deliver value for LLM platform features
- Create top-notch technical documentation, including design docs for internal discussions, engineering docs and tutorials for customers, and compelling data-driven case studies for marketing purposes
- Drive influence through meetings, mentorship, collaboration, and other non-coding activities
Qualification
- Master’s degree with at least 3+ years of experience, or Ph.D. in a relevant field
- Strong technical skills, with a keen eye for API design and a deep understanding of LLM architecture, training, and inference
- Had hands on experience on at least one of the following topics:
- Training: LLM Pretraining, LLM fine-tuning, RLHF, distillation, parameter-efficient methods like LoRA, quantization, etc.
- Inference: Building inference engine / server, Writing optimized kernels, inference + training co-optimizations (speculative decoding), etc.
- Have experience with observability, monitoring, debugging, and measuring success for LLM training / inference systems
- Excellent technical writing skills, with the ability to create clear, concise, and engaging documentation for various audiences
- Proactive and self-driven, with a strong sense of ownership over the systems you work on
- Adaptable to the ever-changing startup environment, embracing pivots and new challenges
- Strong problem-solving skills and the ability to thrive in a collaborative environment
Compensation
- At Anyscale, we take a market-based approach to compensation. We are data-driven, transparent, and consistent. The target salary for this role is $170,112 ~ $237,000. As the market data changes over time, the target salary for this role may be adjusted.
This role is also eligible to participate in Anyscale's Equity and Benefits offerings, including, Stock Options- Healthcare plans, with premiums covered by Anyscale at 99%
- 401k Retirement Plan
- Wellness stipend
- Education stipend
- Paid Parental Leave
- Flexible Time Off
- Commute Reimbursement
- 100% of in office meals covered
Anyscale Inc. is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law.
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