Machine Learning Engineer, Trust & Safety

Anthropic is seeking a Machine Learning Engineer for Trust & Safety to help build safety and oversight mechanisms for their AI systems. The role involves training models to detect harmful behaviors, ensure user well-being, and uphold principles of safety, transparency, and oversight while enforcing terms of service and acceptable use policies.

Key responsibilities include:

• Building ML models to detect unwanted or anomalous behaviors from users and API partners
• Improving automated detection and enforcement systems
• Analyzing user reports of inappropriate accounts and building proactive detection models
• Surfacing abuse patterns to research teams to harden models at the training stage

The ideal candidate should have:

• 4+ years of experience in research/ML engineering or applied research, preferably in trust and safety
• Proficiency in SQL, Python, and data analysis/mining tools
• Experience building trust and safety AI/ML systems (e.g., behavioral classifiers, anomaly detection)
• Strong communication skills to explain complex technical concepts
• Care about societal impacts and long-term implications of their work

Additional valuable experience includes:

• Familiarity with ML frameworks like Scikit-Learn, Tensorflow, or PyTorch
• Experience with high-performance, large-scale ML systems
• Knowledge of language modeling with transformers
• Background in reinforcement learning
• Experience with large-scale ETL

Anthropic offers a competitive compensation package, including salary, equity, and benefits. They provide a collaborative work environment, flexible hours, and the opportunity to work on impactful AI research and development.

The company values diversity and encourages applications from underrepresented groups. They offer visa sponsorship for eligible candidates and have a hybrid work policy requiring at least 25% in-office presence.

Join Anthropic to contribute to the development of safe and beneficial AI systems while working with a committed team of researchers, engineers, and experts in a rapidly growing field.