Senior Manager Data Science

hace 1 día


Madrid, Madrid, España Solera Holdings, LLC. A tiempo completo

Data Science &
Machine Learning Lead
Mission
Leverage AI and Solera's data assets to develop, deliver, operate, and maintain innovative, production-grade components that make vehicle claims and ownership simpler, faster, and more more efficient for customers and users.

What You Will Do

  • Lead technical direction for computer vision–based vehicle damage detection (classification, detection, segmentation), plus tree-based models and LLM-powered components.
  • Own the ML roadmap: translate business goals into measurable technical plans, milestones, and KPIs.
  • Architect scalable data/ML systems on GCP (BigQuery, Dataflow, Vertex AI) to train and serve models across hundreds of millions of images and claims.
  • Guide high-quality delivery in a monorepo: reviews, standards, design docs, testing, reproducibility, and CI/CD.
  • Drive production MLOps: containerization, GKE/Cloud Run, observability (Grafana), cost/performance tuning, SLOs.
  • Shape APIs and services (FastAPI) and internal tools (Streamlit) to accelerate adoption and experimentation.
  • Engage cross-functionally with product and platform to prioritize impact and de-risk delivery.
  • Balance leadership and hands-on work; scope of people management and IC work is adaptable to your strengths.
  • People leadership
  • Manage, coach, and grow ML Engineers; run 1:1s, feedback, and career development.
  • Foster a culture of clarity, ownership, and high standards; set technical bar via mentorship and example.
  • Recruit and onboard top talent; build an inclusive, globally distributed team.

How We Work

  • Monorepo with strong build system, CI/CD, and code quality practices.
  • Freedom to choose the best tool for the job; high autonomy and ownership.
  • Production mindset: reliability, observability, maintainability, measurable impact.

Tech stack

  • Python; TensorFlow, PyTorch
  • GCP: BigQuery, Dataflow, Vertex AI, GKE, Cloud Run, Cloud Deploy
  • Docker, Kubernetes
  • FastAPI, Streamlit
  • Grafana

What You Bring

  • Proven leadership of ML initiatives from problem framing to production at scale.
  • Deep experience with CV models (classification, detection, segmentation) and shipping them with TensorFlow/PyTorch.
  • Strong software engineering and MLOps fundamentals: testing, CI/CD, containers, Kubernetes, monitoring.
  • Expertise with large-scale datasets and distributed processing on GCP (BigQuery, Dataflow) or similar.
  • Experience with tree-based models and integrating LLM APIs into production workflows.
  • Track record of setting technical direction, making pragmatic trade-offs, and delivering measurable outcomes.
  • Structured problem solving, critical thinking, and a driven, ownership-oriented mindset.
  • Effective communication across an internationally distributed team.

Nice to have

  • Vertex AI pipelines.
  • GPU optimization and cost/performance tuning for training/inference.
  • Domain experience in insurance, automotive, or related computer vision applications.

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