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The Machine Learning (ML) Practice team is a highly specialized, collaborative customer-facing ML team at Databricks. We deliver professional services (PS) engagements to help our customers build, scale, and productionize the most cutting-edge ML and GenAI applications. We work cross-functionally to shape long-term strategic priorities and initiatives alongside engineering, product, and developer relations, as well as support internal subject matter expert (SME) teams.
We are looking for a world-class Sr. Manager to lead and grow our EMEA ML Practice. You will report directly to the AVP of Professional Services in EMEA and dotted line to our ML PS Global Leader.
The impact you will have:
- Lead and build a world-class ML + AI practice including hiring, onboarding and scaling of the team across EMEA
- Develop relationships with key customers and partners, scope engagements, and manage escalations to ensure customer success
- Align with the Field Engineering team and Sales Leaders in EMEA (and Global ML practice leadership) on key priorities for ML Services in the region
- Lead strategic PS ML initiatives, practice development, and processes
- Create opportunities for team members to collaborate cross-functionally with R&D to define priorities and influence the product roadmap
- Scale knowledge and best practices across the wider Professional Services team
- Own OKRs for revenue and utilization, with a focus on driving customer outcomes and Databricks consumption
- Raise awareness and be a thought leader in the market by speaking at Databricks and other key ML events
- Lead Databricks cultural values by example and champion the Databricks brand
What we look for:
- Extensive experience managing, hiring, and building a team of motivated data scientists/ML engineers, including establishing programs and processes
- Deep hands-on technical understanding of data science, ML, GenAI and the latest trends
- While managers do not directly deliver customer engagements, we expect that candidates have related past technical experience that allows them to scope engagements and understand issues that arise in project delivery
- Experience building production-grade machine learning deployments on AWS, Azure, or GCP
- Passion for collaboration, life-long learning, and driving business value through ML
- Company first focus and collaborative individuals - we work better when we work together.
- Graduate degree in a quantitative discipline (Computer Science, Engineering, Statistics, Operations Research, etc.) or equivalent practical experience
- [Preferred] Experience working with Databricks and Apache Spark™
- [Preferred] Experience working in a customer-facing role
