Staff ML Inference Engineer - Safety Platform & Scale

Socket.dev; San Francisco (CA); Hybrid; USD 320,000 - 485,000; Full time

Benefits offered by this job

Equity donation matching

Generous vacation

Parental leave

Flexible hours

SF office access

Job summary

Anthropic is seeking engineers to design, build, and operate production ML infrastructure that powers Claude's safety systems. You will work at the intersection of ML, distributed systems, and AI safety to scale classifiers and ML defenses across platforms.

The role emphasizes reliability, collaboration with researchers, and delivering production-ready safety tooling. Strong candidates will have 5+ years in production ML infrastructure, experience with transformers, monitoring systems, and

Qualifications

• Proficient in Python and ML frameworks like PyTorch, TensorFlow, or JAX.
• Understand distributed systems principles and have built systems that handle high-throughput, low-latency workloads.
• Have built automated or self-service deployment pipelines and eval infrastructure allowing researchers to roll out classifiers and models independently.
• Have implemented A/B testing frameworks and experimentation infrastructure for ML systems.
• Are results-oriented, with a bias towards reliability and impact in safety-critical systems.
• Enjoy collaborating with researchers and translating cutting-edge research into production systems.
• Care deeply about AI safety and the societal impacts of your work.

Responsibilities

• Design and build scalable ML infrastructure to support real-time safety deployments across our classifier and model ecosystem
• Build monitoring and observability tools to track classifier performance, data quality, and system health for safety-critical applications
• Collaborate with research teams to productionize safety research, translating experimental safety techniques into robust, scalable systems
• Optimize inference latency and throughput for real-time safety evaluations while maintaining high reliability standards
• Implement automated testing, deployment, and rollback systems for ML models in production safety applications
• Partner with Safeguards, Security, and Alignment teams to understand requirements and deliver infrastructure that meets safety and production needs
• Contribute to the development of internal tools and frameworks that accelerate safety research and deployment

Skills

Python

ML frameworks

Distributed systems

Deployment pipelines

A/B testing

Safety research collaboration

Education

Bachelor's degree

Job description

Anthropic is seeking engineers to design, build, and operate production ML infrastructure that powers Claude's safety systems. You will work at the intersection of ML, distributed systems, and AI safety to scale classifiers and ML defenses across platforms.

The role emphasizes reliability, collaboration with researchers, and delivering production-ready safety tooling. Strong candidates will have 5+ years in production ML infrastructure, experience with transformers, monitoring systems, and