What are the responsibilities and job description for the Machine Learning Engineer, Trust & Safety position at Anthropic?
About the role
We are looking for ML engineers to help build safety and oversight mechanisms for our AI systems. As a Trust and Safety Machine Learning Engineer, you will work to train models which detect harmful behaviors and help ensure user well-being. You will apply your technical skills to uphold our principles of safety, transparency, and oversight while enforcing our terms of service and acceptable use policies.
Responsibilities:
- Build machine learning models to detect unwanted or anomalous behaviors from users and API partners, and integrate them into our production system
- Improve our automated detection and enforcement systems as needed
- Analyze user reports of inappropriate accounts and build machine learning models to detect similar instances proactively
- Surface abuse patterns to our research teams to harden models at the training stage
You may be a good fit if you:
- Have 4 years of experience in a research/ML engineering or an applied research scientist position, preferably with a focus on trust and safety.
- Have proficiency in SQL, Python, and data analysis/data mining tools.
- Have proficiency in building trust and safety AI/ML systems, such as behavioral classifiers or anomaly detection.
- Have strong communication skills and ability to explain complex technical concepts to non-technical stakeholders.
- Care about the societal impacts and long-term implications of your work.
Strong candidates may also have experience with:
- Machine learning frameworks like Scikit-Learn, TensorFlow, or PyTorch
- High-performance, large-scale ML systems
- Language modeling with transformers
- Reinforcement learning
- Large-scale ETL
