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