Character.AI Logo

Character.AI

Research Engineer, ML Systems (All Industry Levels)

Job Posted 3 Days Ago Posted 3 Days Ago
Be an Early Applicant
2 Locations
Expert/Leader
2 Locations
Expert/Leader
As a Research Engineer on the ML Systems team, you will optimize GPU performance for AI models, develop training and inference systems, and contribute to groundbreaking AI advancements.
The summary above was generated by AI

About the role and team

Joining us as a Research Engineer on the ML Systems team, you’ll be working on cutting-edge ML training and inference systems, optimizing the performance and efficiency of our GPU clusters, and developing new technologies that fine-tune leading consumer AI models with a data flywheel, and serve 20K+ QPS in production with LLMs. Your work will directly contribute to our groundbreaking advancements in AI, helping shape an era where technology is not just a tool, but a companion in our daily lives. At Character.AI, your talent, creativity, and expertise will not just be valued—they will be the catalyst for change in an AI-driven future.

What you'll do

The ML Systems team is responsible for the research and deployment of systems that efficiently utilize GPU for AI-enabled products. 

As a research engineer, you will work across teams and our technical stack to improve our training performance and inference runtime. You will get to shape the conversational experience of millions of users per day.

Example projects:

  • Write efficient Triton kernels and tune them for our specific models and hardware

  • Develop prefix-aware routing algorithms to improve serving cache hit rate

  • Train and distill LLMs to improve latency while preserving accuracy and engagements

  • Build an efficient and scalable distributed RLHF stack powering the model innovations

  • Develop systems for efficient multimodal (image gen/video gen) model training & inference

Who you are

  • "All Industry Levels": at least PhD (or equivalent) research experience

  • Write clear and clean production system code

  • Strong understanding of modern machine learning techniques (reinforcement learning, transformers, etc)

  • Track record of exceptional research or creative ML systems projects

  • Comfortable writing model development code (PyTorch) for either training or inference

Nice to Have

  • Experience training large models in a distributed setting utilizing PyTorch distributed, DeepSpeed, Megatron.

  • Experience working with GPUs & collectives (training, serving, debugging) and writing kernels (Triton, CUDA, CUTLASS).

  • Experience with LLM inference systems and literature such as vLLM and FlashAttention.

  • Familiarity with ML deployment and orchestration (Kubernetes, Docker, cloud)

  • Publications in relevant academic journals or conferences in the field of machine learning and systems

About Character.AI

Character.AI empowers people to connect, learn and tell stories through interactive entertainment. Over 20 million people visit Character.AI every month, using our technology to supercharge their creativity and imagination. Our platform lets users engage with tens of millions of characters, enjoy unlimited conversations, and embark on infinite adventures.


In just two years, we achieved unicorn status and were honored as Google Play's AI App of the Year—a testament to our innovative technology and visionary approach.


Join us and be a part of establishing this new entertainment paradigm while shaping the future of Consumer AI!

At Character, we value diversity and welcome applicants from all backgrounds. As an equal opportunity employer, we firmly uphold a non-discrimination policy based on race, religion, national origin, gender, sexual orientation, age, veteran status, or disability. Your unique perspectives are vital to our success.

Top Skills

Cuda
Cutlass
Deepspeed
Docker
Gpu
Kubernetes
Megatron
Ml
PyTorch
Triton

Character.AI Menlo Park, California, USA Office

700 El Camino Real, Menlo Park, California, United States, 94025

Similar Jobs

An Hour Ago
Hybrid
2 Locations
Mid level
Mid level
Fintech • HR Tech • Software
As a Developer Success Engineer, you'll guide customers through API integration, troubleshoot technical issues, and enhance user experience through feedback-driven solutions and documentation improvements.
Top Skills: AWSNode.jsPostgressqlRedis
2 Hours Ago
Hybrid
New York, NY, USA
246K-281K Annually
Senior level
246K-281K Annually
Senior level
Fintech • Machine Learning • Payments • Software • Financial Services
Lead a team of mobile developers in building iOS applications, mentor junior engineers, and ensure high-quality delivery through agile practices.
Top Skills: AgileiOSKotlinOpen Source FrameworksSwift
2 Hours Ago
Hybrid
New York, NY, USA
211K-241K Annually
Mid level
211K-241K Annually
Mid level
Fintech • Machine Learning • Payments • Software • Financial Services
Lead the development of Android applications at Capital One, collaborating with cross-functional teams and mentoring juniors. Focus on best practices and agile methodologies.
Top Skills: AgileAndroidAPIsiOSKotlinWeb Technologies

What you need to know about the San Francisco Tech Scene

San Francisco and the surrounding Bay Area attracts more startup funding than any other region in the world. Home to Stanford University and UC Berkeley, leading VC firms and several of the world’s most valuable companies, the Bay Area is the place to go for anyone looking to make it big in the tech industry. That said, San Francisco has a lot to offer beyond technology thanks to a thriving art and music scene, excellent food and a short drive to several of the country’s most beautiful recreational areas.

Key Facts About San Francisco Tech

  • Number of Tech Workers: 365,500; 13.9% of overall workforce (2024 CompTIA survey)
  • Major Tech Employers: Google, Apple, Salesforce, Meta
  • Key Industries: Artificial intelligence, cloud computing, fintech, consumer technology, software
  • Funding Landscape: $50.5 billion in venture capital funding in 2024 (Pitchbook)
  • Notable Investors: Sequoia Capital, Andreessen Horowitz, Bessemer Venture Partners, Greylock Partners, Khosla Ventures, Kleiner Perkins
  • Research Centers and Universities: Stanford University; University of California, Berkeley; University of San Francisco; Santa Clara University; Ames Research Center; Center for AI Safety; California Institute for Regenerative Medicine
By clicking Apply you agree to share your profile information with the hiring company.

Sign up now Access later

Create Free Account

Please log in or sign up to report this job.

Create Free Account