Research Engineer / Research Scientist, Multimodal

Anthropic Anthropic · AI Frontier · AI Research & Engineering

Research Engineer/Scientist focused on building and studying multimodal AI systems, including training, inference, system design, and data collection. The role involves developing new architectures, reinforcement learning environments, high-performance serving infrastructure, and data processing tools for multimodal data.

What you'd actually do

  1. We develop new architectures for modeling multimodal data and study how they interact with text-only models at scale.
  2. Complex multimodal reinforcement learning environments.
  3. High-performance RPC servers for processing image inputs.
  4. Sandboxing infrastructure for securely collecting data.
  5. We develop tooling to collect, process and clean multimodal data at scale.

Skills

Required

  • significant software engineering experience
  • high performance, large-scale ML systems
  • language modeling with transformers
  • reinforcement learning

Nice to have

  • GPUs
  • Kubernetes
  • Pytorch
  • OS internals
  • Bachelor's degree in a related field or equivalent experience

What the JD emphasized

  • multimodal models
  • training
  • inference
  • system design
  • data collection
  • new architectures
  • complex multimodal reinforcement learning environments
  • high-performance RPC servers for processing image inputs
  • sandboxing infrastructure for securely collecting data
  • tooling to collect, process and clean multimodal data at scale
  • significant software engineering experience
  • high performance, large-scale ML systems
  • language modeling with transformers
  • reinforcement learning

Other signals

  • multimodal models
  • training
  • inference
  • system design
  • data collection
  • new architectures
  • complex multimodal reinforcement learning environments
  • high-performance RPC servers for processing image inputs
  • sandboxing infrastructure for securely collecting data
  • tooling to collect, process and clean multimodal data at scale