Machine Learning Engineer, Trust & Safety
About Anthropic
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.
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
The expected salary range for this position is:
Logistics
Location-based hybrid policy: Currently, we expect all staff to be in one of our offices at least 25% of the time. However, some roles may require more time in our offices.
Visa sponsorship: We do sponsor visas! However, we aren't able to successfully sponsor visas for every role and every candidate. But if we make you an offer, we will make every reasonable effort to get you a visa, and we retain an immigration lawyer to help with this.
We encourage you to apply even if you do not believe you meet every single qualification. Not all strong candidates will meet every single qualification as listed. Research shows that people who identify as being from underrepresented groups are more prone to experiencing imposter syndrome and doubting the strength of their candidacy, so we urge you not to exclude yourself prematurely and to submit an application if you're interested in this work. We think AI systems like the ones we're building have enormous social and ethical implications. We think this makes representation even more important, and we strive to include a range of diverse perspectives on our team.
How we're different
We believe that the highest-impact AI research will be big science. At Anthropic we work as a single cohesive team on just a few large-scale research efforts. And we value impact — advancing our long-term goals of steerable, trustworthy AI — rather than work on smaller and more specific puzzles. We view AI research as an empirical science, which has as much in common with physics and biology as with traditional efforts in computer science. We're an extremely collaborative group, and we host frequent research discussions to ensure that we are pursuing the highest-impact work at any given time. As such, we greatly value communication skills.
The easiest way to understand our research directions is to read our recent research. This research continues many of the directions our team worked on prior to Anthropic, including: GPT-3, Circuit-Based Interpretability, Multimodal Neurons, Scaling Laws, AI & Compute, Concrete Problems in AI Safety, and Learning from Human Preferences.
Come work with us!
Anthropic is a public benefit corporation headquartered in San Francisco. We offer competitive compensation and benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and a lovely office space in which to collaborate with colleagues.
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