# Machine Learning Infrastructure Engineer, Safeguards Research

**Company:** [Anthropic](https://hotfix.jobs/companies/anthropic)
**Location:** San Francisco, CA, New York, NY
**Role:** ML Engineering
**Salary:** $350k – $500k/yr
**Experience:** 5+ years
**Skills:** Python, Distributed Systems, Data Pipelines, machine learning infrastructure, Transformers, gpu programming, inference optimization, experiment tracking, evaluation harnesses, probes, interpretability
**Posted:** 2026-07-21

> Build and own ML infrastructure, data pipelines, and tooling for Safeguards research at Anthropic. Focus on fast researcher iteration for training/evaluating lightweight detectors on model internals while ensuring correctness at scale. Requires strong Python, distributed systems, and production infrastructure experience.

## Job Description

## Key Responsibilities
- Build and scale the infrastructure and data pipelines behind Safeguards machine learning research
- Own the training, evaluation, and scoring workflows researchers use, with a focus on cutting the time between an idea and a result
- Design tooling and interfaces, including libraries and command line tools, that researchers can use directly without needing to understand the systems underneath
- Build correctness and sanity checking into the stack, so results stay trustworthy as models and workloads evolve
- Take the highest-value research workflows from experiments to reliable, production-grade jobs
- Improve the throughput, cost, and reliability of large-scale inference and scoring workloads
- Partner closely with researchers and engineers across Safeguards to understand their workflows, anticipate how their needs will change, and design for that ahead of time

## Minimum Qualifications
- Strong software engineering fundamentals and hands-on coding ability, with proficiency in Python
- Experience building and operating data-intensive or distributed systems in production
- Experience building tooling or infrastructure that other engineers or researchers use as a dependency
- Comfort working across the research-to-deployment pipeline, from exploratory experiments to production systems
- Ability to debug performance and correctness problems across an unfamiliar stack
- Strong written and verbal communication skills, and a collaborative approach to technical decisions

## Preferred Qualifications
- Experience with high-performance, large-scale machine learning systems
- Familiarity with language modeling and transformers, including working with model internals
- Experience with machine learning framework internals, GPU or accelerator programming, or inference optimization
- Experience building experiment tracking, caching layers, or evaluation harnesses for research teams
- Experience with probes, interpretability, or classifier development
- Interest in the misuse risks of AI systems and a desire to work on mitigating them

## Education
- Bachelor’s degree or an equivalent combination of education, training, and/or experience in a field relevant to the role

## Similar roles

- [Software Engineer, Research Acceleration](https://hotfix.jobs/jobs/12f9a314-7f22-49c4-8194-f1af829f0f58) - Thinking Machines Lab - San Francisco, CA - $350k – $475k/yr
- [Research Infrastructure Engineer](https://hotfix.jobs/jobs/ea3efdd7-00d7-492b-a405-ceec9a86fd52) - Thinking Machines Lab - San Francisco, CA - $350k – $475k/yr
- [Research Engineer, Safeguards Labs](https://hotfix.jobs/jobs/a962ca34-7b12-4833-910e-5978ec8a9136) - Anthropic - San Francisco, CA - $350k – $850k/yr
- [Research Engineer, Knowledge Team](https://hotfix.jobs/jobs/c13da357-5862-462d-b466-8d7cc4653365) - Anthropic - San Francisco, CA - $350k – $850k/yr
- [Research, Vision Expertise](https://hotfix.jobs/jobs/c69bae12-1a50-49e9-8482-14ff5bfdb088) - Thinking Machines Lab - San Francisco, CA - $350k – $475k/yr

**Apply:** https://hotfix.jobs/jobs/1b6b27bd-8416-45da-b2b5-eddcaa1d8e2d
**Canonical:** https://hotfix.jobs/jobs/1b6b27bd-8416-45da-b2b5-eddcaa1d8e2d