Data Science Team Lead

Há 6 dias


Lisboa, Lisboa, Portugal PagerDuty, Inc. Tempo inteiro

PagerDuty's Operations Cloud powers the agility that drives digital transformation. We're looking for a skilled Staff Machine Learning (ML) Engineer to join our AI group and lead the development of AI-first solutions.

In this role, you'll be responsible for architecting state-of-the-art AI initiatives, mentoring junior team members, and contributing to the development of our data platform.

With a focus on innovation and collaboration, you'll work closely with cross-functional teams to ensure successful project outcomes and drive the adoption of best practices across the organization.

Responsibilities:
  • Data Platform Development: Build and improve the capabilities of our data platform to support the production of ML/AI-based solutions.
  • AI/ML Adoption: Drive the adoption of AI/ML standards across the organization, ensuring seamless integration and collaboration.
  • Team Guidance: Provide technical leadership and mentoring to junior team members, driving growth and excellence.
  • Collaboration: Work closely with cross-functional teams to ensure successful project outcomes.
  • Improvement Focus: Identify opportunities for improvement and implement new approaches to address systemic pain points and technical debt.
Requirements:
  • You have 8+ years of experience building, designing, and evolving data architecture for large-scale systems.
  • Excellent communication skills, with the ability to effectively collaborate with cross-functional teams.
  • Experience working with Product teams, ensuring timely delivery and successful project outcomes.
  • A deep understanding of the trade-offs involved in designing and delivering machine learning solutions to production.
  • Experience leading cross-team architecture discussions, building technical prototypes, and driving the adoption of best practices across diverse teams.
  • Demonstrated expertise in data engineering processes, working with unstructured data and cloud-based data infrastructures.
  • A passion for ML engineering, with a desire to drive discussions with stakeholders and executives.

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