Description
The Risk Automation ML team at Block automates Risk and Compliance investigations and decision making through the application of agentic and generative AI technology.
You will experiment and deploy AI copilot and autopilot systems at scale to improve analyst productivity and/or eliminate manual decision loops altogether.
Responsibilities:
- Own the end-to-end system including API calls to disparate data sources, advanced prompt tuning, orchestration, metrics and evaluation, productionization, and monitoring.
- Leverage diverse data sets to build transformer-based ML models to improve downstream detection tasks.
- Work cross-functionally with product, platform, engineering, and operational stakeholders to deploy production-grade systems and monitor and tune ongoing performance.
- Use Python ML stack, LLMs, Pytorch, Snowflake, Airflow-based tools, data platform, and cloud services (both GCP & AWS) to get the job done.
- Leverage agentic tools (Claude Code/Codex/Openclaw) to supercharge research, development, devOps, and documentation work.
Requirements:
- 8+ years of Machine Learning modeling experience.
- Full stack ML experience is strongly preferred.
- A Masters or advanced degree in computer science, data science, operations research, applied math, stats, physics, or a related technical field.
- 3+ yrs experience with AI engineering, Large language models, and a background in traditional NLP techniques is a strong plus for this role.
- End-to-end experience of building and deploying ML/AI to production systems (batch and real-time) that are performant at scale.
- Experience of independently owning, influencing, and driving programs with multiple cross-functional stakeholders that have significant business impact.
Benefits:
- Remote work
- Medical insurance
- Flexible time off
- Retirement savings plans
- Modern family planning