# [C] Research Engineer, Discovery

**Company**: Anthropic
**Location**: San Francisco, CA
**Work arrangement**: hybrid
**Experience**: senior
**Job type**: full-time
**Salary**: $350,000-$850,000 USD
**Category**: Engineering
**Industry**: Technology
**Wikidata**: https://www.wikidata.org/wiki/Q116758847

**Apply**: https://job-boards.greenhouse.io/anthropic/jobs/5467305008?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply
**Canonical**: https://yubhub.co/job/c-research-engineer-discovery-c2ad9fed-865/

## Description

Anthropic's mission is to create reliable, interpretable, and steerable AI systems.

As a Research Engineer on our team you will work end to end across the whole model stack, identifying and addressing key infra blockers on the path to scientific AGI.

## Responsibilities:

- Design and implement large-scale infrastructure systems to support AI scientist training, evaluation, and deployment across distributed environments

- Identify and resolve infrastructure bottlenecks impeding progress toward scientific capabilities

- Develop robust and reliable evaluation frameworks for measuring progress towards scientific AGI

- Build scalable and performant VM/sandboxing/container architectures to safely execute long-horizon AI tasks and scientific workflows

- Collaborate to translate experimental requirements into production-ready infrastructure

- Develop large scale data pipelines to handle advanced language model training requirements

- Optimize large scale training and inference pipelines for stable and efficient reinforcement learning

## Requirements:

- 6+ years of highly-relevant experience in infrastructure engineering with demonstrated expertise in large-scale distributed systems

- Strong communicator and enjoy working collaboratively

- Deep knowledge of performance optimization techniques and system architectures for high-throughput ML workloads

- Experience with containerization technologies (Docker, Kubernetes) and orchestration at scale

- Proven track record of building large-scale data pipelines and distributed storage systems

- Excel at diagnosing and resolving complex infrastructure challenges in production environments

- Can work effectively across the full ML stack from data pipelines to performance optimization

- Experience collaborating with other researchers to scale experimental ideas

- Thrive in fast-paced environments and can rapidly iterate from experimentation to production

## Nice to Have:

- Experience with language model training infrastructure and distributed ML frameworks (PyTorch, JAX, etc.)

- Background in building infrastructure for AI research labs or large-scale ML organizations

- Knowledge of GPU/TPU architectures and language model inference optimization

- Experience with cloud platforms (AWS, GCP) at enterprise scale

- Familiarity with VM and container orchestration

- Experience with workflow orchestration tools and experiment management systems

- History working with large scale reinforcement learning

- Comfort with large scale data pipelines (Beam, Spark, Dask, …)

The annual compensation range for this role is $350,000-$850,000 USD.

For more fresh new jobs, check out [yubhub.co](https://yubhub.co/).

## Skills

### Required
- large-scale distributed systems
- infrastructure engineering
- performance optimization
- containerization technologies
- data pipelines
- ML stack

### Nice to have
- language model training infrastructure
- distributed ML frameworks
- GPU/TPU architectures
- cloud platforms
- workflow orchestration tools
- reinforcement learning

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Source: [Apply at job-boards.greenhouse.io](https://job-boards.greenhouse.io/anthropic/jobs/5467305008?utm_source=yubhub.co&utm_medium=jobs_feed&utm_campaign=apply)