ML Infrastructure Engineer, Safeguards
Location
San Francisco, California, United States
Work type
Hybrid
Employment
Full Time
Experience
5+ years
Compensation
$320K - $405K per year
Posted
2h ago
Summary and responsibilities
Role overview
Summary
As a Machine Learning Infrastructure Engineer in the Safeguards organization, you will design, build, and scale critical infrastructure for AI safety systems. This role involves working at the intersection of machine learning, distributed systems, and AI safety to ensure reliable and trustworthy AI models.
About the role
We are seeking a Machine Learning Infrastructure Engineer to join our Safeguards organization, where you'll build and scale the critical infrastructure that powers our AI safety systems. You'll work at the intersection of machine learning, large-scale distributed systems, and AI safety, developing the platforms and tools that enable our safeguards to operate reliably at scale.
As part of the Safeguards team, you'll design and implement ML infrastructure that powers Claude safety. Your work will directly contribute to making AI systems more trustworthy and aligned with human values, ensuring our models operate safely as they become more capable.
Responsibilities:
Design and build scalable ML infrastructure to support real-time and batch classifier and safety evaluations across our model ecosystem
Build monitoring and observability tools to track model 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
You may be a good fit if you:
Have 5+ years of experience building production ML infrastructure, ideally in safety-critical domains like fraud detection, content moderation, or risk assessment
Are proficient in Python and have experience with ML frameworks like PyTorch, TensorFlow, or JAX
Have hands-on experience with cloud platforms (AWS, GCP) and container orchestration (Kubernetes)
Understand distributed systems principles and have built systems that handle high-throughput, low-latency workloads
Have experience with data engineering tools and building robust data pipelines (e.g., Spark, Airflow, streaming 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
Strong candidates may have experience with:
Working with large language models and modern transformer architectures
Implementing A/B testing frameworks and experimentation infrastructure for ML systems
Developing monitoring and alerting systems for ML model performance and data drift
Building automated labeling systems and human-in-the-loop workflows
Experience in trust & safety, fraud prevention, or content moderation domains
Knowledge of privacy-preserving ML techniques and compliance requirements
Contributing to open-source ML infrastructure projects
Updated 2h ago
Candidate fit
Skills and qualifications
Additional skills
Experience
5+ years
How this role is positioned
Role classification
Job domains
Industries
Employment
Full Time
Contract duration
Permanent
Hiring type
Direct
Global hiring
Location specific
Offer details
Compensation and benefits
Compensation
$320K - $405K per year
Benefits and perks
Location, schedule, and role shape
Work setup
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Context on the employer
Company snapshot
Company
Anthropic
Team size
Growing team
Location
San Francisco, California, United States
Anthropic’s mission is to create reliable, interpretable, and steerable AI systems. We want AI to be safe and beneficial for our users and for society as a whole. Our team is a quickly growing group of committed researchers, engineers, policy experts, and business leaders working together to build beneficial AI systems.
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ML Infrastructure Engineer, Safeguards
San Francisco, California, United States • Full Time