Staff+ Software Engineer (ML Inference)

Location: San Francisco, CA; hybrid policy requiring staff to be in an office at least 25% of the time

Annual salary: $320,000–$485,000 USD

Company

Anthropic develops reliable, interpretable, and steerable AI systems, with a focus on AI safety and beneficial applications of AI.

What you will do

• Design and build scalable ML infrastructure for real-time safety deployments across classifiers and models.
• Develop monitoring and observability tools for classifier performance, data quality, and system health.
• Translate safety research and experimental techniques into robust, scalable production systems.
• Optimize inference latency and throughput while maintaining reliability for safety-critical evaluations.
• Implement automated testing, deployment, experimentation, and rollback systems for production ML models.
• Collaborate with Safeguards, Security, Alignment, and research teams on infrastructure and internal tooling.

Requirements

• Proficiency in Python and experience with ML frameworks such as PyTorch, TensorFlow, or JAX.
• Strong 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 or experimentation infrastructure for ML systems.
• Bachelor’s degree or equivalent education, training, or professional experience in a relevant field.
• Strong interest in AI safety, reliability, and the societal impact of AI systems.

Nice to have

• 5+ years of experience building production ML infrastructure, particularly in safety-critical domains.
• Experience with large language models and transformer architectures.
• Experience developing ML monitoring, alerting, and data-drift detection systems.
• Background in trust and safety, fraud prevention, content moderation, or privacy-preserving ML.

Culture & Benefits

• Collaborative research environment focused on a small number of large-scale AI efforts.
• Flexible working hours and an office environment designed for collaboration.
• Generous vacation and parental leave.
• Competitive compensation, benefits, and optional equity donation matching.
• Visa sponsorship is available, although eligibility depends on the role and candidate.