4 hours ago
Base Salary
$320k - $485k/yr
Responsibilities
- Build and operate a feature computation platform for model training and low-latency real-time scoring.
- Train, evaluate, and deploy models that detect account-level abuse and fraud in offline and online environments.
- Automate feature development, model training, and evaluation workflows, including use of Claude.
- Establish backtesting, shadow deployment, staged rollout, and monitoring for skew, drift, and adversarial adaptation.
- Improve label coverage and quality with data scientists and the Policy & Enforcement team.
- Partner with product and platform teams to integrate model decisions while minimizing latency, stability, and architectural impact.
Requirements
- Proficiency in Python and SQL.
- Experience training machine learning models and deploying them to production.
- Experience building data pipelines with a batch processing engine such as Spark or Beam and a workflow scheduler such as Airflow.
- Working understanding of point-in-time correctness and training/serving skew and how to prevent them.
- Strong communication skills and ability to explain technical tradeoffs to non-technical stakeholders.
- Bachelor’s degree or an equivalent combination of education, training, and/or experience in a relevant field.
- Preferred qualifications include experience with feature platforms, stream processing, production fraud/risk/ranking models, tree-based models, clustering or graph-based detection, integrity or abuse detection, scarce or noisy labels, and AutoML.
Benefits
- Annual compensation range is $320,000—$485,000 USD.
- Hybrid policy currently expects staff to work from an office at least 25% of the time, with some roles requiring more.
- Visa sponsorship is offered with reasonable efforts made after an offer, though sponsorship cannot be successfully provided for every role or candidate.
- Benefits include competitive benefits, optional equity donation matching, generous vacation and parental leave, flexible working hours, and office collaboration space.
Tech Stack
Categories
Data EngineeringML Engineering
About Anthropic
Anthropic builds large language models and the Claude AI assistant for developers and enterprises, offered via API access and enterprise plans. Founded in 2021 and headquartered in San Francisco, it distributes Claude through its own platform and via partners such as Amazon Bedrock and Google Cloud’s Vertex AI. Its work emphasizes model reliability, interpretability, and practical tooling for tasks like coding assistance, analysis, and customer support automation.