Insider Risk Rules & Reporting Developer responsible for designing and maintaining insider risk detection rules. Collaborating with various departments to ensure security and compliance in risk management at TD.
About the role
- Head of Forward-Deployed Engineering leading teams at Snorkel AI. Focusing on data delivery and ML workflows in hybrid work setting.
Responsibilities
- Build and lead the Forward Deployed Engineering DaaS organization, setting a clear vision, defining the operating model and scaling its impact across Snorkel’s Expert Data-as-a-Service workflows
- Build, mentor, and motivate high performing teams, including cultivating skills and culture needed to consistently deliver exceptional outcomes and transformative impact.
- Own and evolve the data pipeline components of the DaaS stack, including model-assisted labeling, quality estimation, and data-centric feedback loops that guide human input
- Partner with customers - including research and engineering teams at Frontier AI Labs - to scope requirements for complex, novel AI datasets and translate needs into delivery-ready workflows
- Establish and execute scalable processes for data generation and validation, quality measurement, and delivery-readiness across a range of annotation projects
- Develop robust systems for request intake, task orchestration, SLA tracking, and progress monitoring to ensure seamless execution and prevent critical delivery gaps
- Prototype and deploy LLM-based workflows to assess annotation quality, augment human review and data generation, and accelerate delivery timelines
- Collaborate cross-functionally with research and engineering teams to innovate, develop, and productionize HITL data generation methods, advanced quality techniques, and improve internal delivery tooling
- Drive continuous improvement by developing reusable workflows, surfacing operational insights, and enabling the organization to scale faster while maintaining high quality
Requirements
- 7+ years of experience in applied data or ML engineering roles, including 2+ years leading high-performing technical teams in hands-on management capacity
- Demonstrated success in customer facing roles, with a strong enthusiasm for data pipelines and LLM-based workflows.
- Proven track record of managing technical field teams in fast-paced, delivery-focused environments with competing priorities
- Experience as a player-coach—comfortable being hands-on while supporting and scaling the team
- Proven ability to thrive in fast-paced, ambiguous environments with cross-functional stakeholders
- Strong practical experience with LLM-based workflows, Python, SQL, and data tooling (e.g., pandas, Plotly, Streamlit, Dash)
- Bonus: experience working with labeling workflows or internal tooling for data delivery orgs
Benefits
- All offers also include equity in the form of employee stock options
Job title
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Experience level
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Degree requirement
No Education Requirement
Tech skills
Location requirements
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