Anthropic Software Engineer

You may be a good fit if you:

• Have significant software engineering experience
• Are results-oriented, with a bias towards flexibility and impact
• Pick up slack, even if it goes outside your job description
• Enjoy pair programming (we love to pair!)
• Want to learn more about machine learning research
• Care about the societal impacts of your work

Strong candidates may also have experience with:

• High performance, large-scale ML systems
• GPUs, Kubernetes, Pytorch, or OS internals
• Language modeling with transformers
• Reinforcement learning
• Large-scale ETL
• Security and privacy best practice expertise
• Machine learning infrastructure like GPUs, TPUs, or Trainium, as well as supporting networking infrastructure like NCCL
• Low level systems, for example linux kernel tuning and eBPF 
• Technical expertise: Quickly understanding systems design tradeoffs, keeping track of rapidly evolving software systems

Representative projects:

• Optimizing the throughput of a new attention mechanism
• Comparing the compute efficiency of two Transformer variants
• Making a Wikipedia dataset in a format models can easily consume
• Scaling a distributed training job to thousands of GPUs
• Writing a design doc for fault tolerance strategies
• Creating an interactive visualization of attention between tokens in a language model

Deadline to apply: None. Applications will be reviewed on a rolling basis.