Anthropic
Staff+ Software Engineer, ML Inference Path
$320K–$485K
San Francisco, CA +1 · Staff · Full-time · Posted Sep 9, 2026
- Location
- San Francisco, CA
San Francisco, California, United States - Experience
- Minimum years correlate with internal job level requirements; strong candidates may have 5+ years of production ML infrastructure experience.
- Education
- Bachelor’s degree or an equivalent combination of education, training, and/or experience; relevant field of study demonstrated through coursework, training, or professional experience.
- Visa sponsorship
- Visa sponsorship is available, but not for every role or candidate; if an offer is made, Anthropic will make every reasonable effort to obtain a visa.
About the job
Build and operate scalable production infrastructure that deploys ML-based safety classifiers and defenses across Claude’s inference path.
What you'll do
- Design scalable infrastructure, monitoring, observability, and automated deployment systems for safety models.
- Productionize safety research and optimize inference latency, throughput, reliability, and rollback processes.
- Collaborate with Safeguards, Security, Alignment, research, and inference teams; develop internal tools for safety research and deployment.
What they ask for
- Proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or JAX.
- Understanding of distributed systems and experience building high-throughput, low-latency systems.
- Experience building automated or self-service deployment pipelines and evaluation infrastructure for ML models.
- Experience implementing A/B testing and experimentation infrastructure for ML systems.
Nice to have
- 5+ years building production ML infrastructure, ideally in safety-critical domains.
- Experience with LLMs and transformers, model monitoring and data drift, trust and safety, fraud prevention, content moderation, privacy-preserving ML, or compliance.
Pay
$320,000 — $485,000 USD (base salary)
Tools
Python, PyTorch, TensorFlow, JAX
AI focus
Productionize ML-based safety classifiers and defenses for Claude, supporting real-time safety evaluations and safety research deployment.
Model-written summary · the original posting is authoritative