Research Engineer, Character.ai
Machine Learning Systems, All Industry Levels
$225-400k
AI natural language chatbot
Open for applications
AI natural language chatbot
101-200 employees
Open for applications
$225-400k
101-200 employees
Company mission
To empower everyone with Artificial General Intelligence (AGI).
Role
Who you are
- 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
What the job involves
- 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
- 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
- "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
Our take
Search engines have long been a boon to productivity, but a long period of heavy advertising, content and SEO spam and malicious actors have limited the effectiveness of traditional keyword searching. Recently, conversational AI assistants have arrived, allowing non-specialists to navigate an increasingly difficult sea of data and return with relevant information, presented in a usable and sometimes very entertaining way.
Character.ai is one of the more recent entries in this increasingly crowded field that has only grown more heated since the public release of ChatGPT in late 2022. However, compared to Microsoft and OpenAI's offerings, Character.ai stands out with a more playful personality - its bots can mimic the voices of celebrities, historical persons and popular characters. This has led to users spending vastly more time interacting with Character.ai's bots compared to the competition: nearly three times longer on average than with ChatGPT, for instance.
Following a period of rapid user growth, Character.ai closed a major funding round at a valuation exceeding $1 billion. While it is currently enjoying meteoric success, in the longer term, Character.ai's challenge is to develop a funding model that will give it the staying power it will need to compete against OpenAI and other major firms in the market. A solution it is currently exploring is research-based partnerships with large companies such as Musk's xAI and Meta.
Kirsty
Company Specialist at Welcome to the Jungle
Insights
Few candidates hear
back within 2 weeks
Company
Funding (1 round)
Mar 2023
$150m
SERIES A
Total funding: $150m
Company HQ
Menlo Park, CA
Articles
Leadership
Noam Shazeer
(CEO)Previously worked at Google for almost 20 years as a Software Engineer then Principal Software Engineer.
Daniel De Freitas
(President)Before co-founding Character.ai was a Senior Staff Software Engineer for Google. Prior to that, they were a Software Engineer at Microsoft.
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