Machine Learning Engineer – AI Core
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
- Design, train, and ship computer vision models for vehicle damage detection (classification, detection, segmentation), as well as tree-based models and LLM-powered components.
- Build scalable data and ML pipelines on GCP (BigQuery, Dataflow, Vertex AI) for training, evaluation, and inference at scale across hundreds of millions of images and claims.
- Deploy and operate services on GKE/Cloud Run with Docker and Kubernetes, following CI/CD with robust build systems and testing.
- Expose models via FastAPI; build internal tools and demos with Streamlit; instrument monitoring and alerting with Grafana.
- Own the end-to-end lifecycle: problem framing, data curation, experimentation, model/productization, performance/cost optimization, and post-deployment monitoring.
- Contribute to a high-quality monorepo: code reviews, standards, documentation, testing, and reproducibility.
- Collaborate in an internationally distributed team, driving clarity, sharing best practices, and improving ML/engineering workflows.
How we work
Monorepo with strong build, CI/CD, and code quality practices.
Freedom to choose the best tool for the job; high autonomy and ownership.
Production mindset: reliability, observability, maintainability, and 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
- Strong Python and software engineering fundamentals (testing, code quality, CI/CD, performance).
- Proven experience training and deploying CV models (classification, detection, segmentation) with TensorFlow/PyTorch.
- Proficiency with large-scale datasets and distributed processing on GCP (BigQuery, Dataflow) or similar.
- Production MLOps experience on Kubernetes/containers.
- Ability to design clean APIs and services (FastAPI) and build usable internal tools (Streamlit).
- Experience with tree-based models.
- Experience with integrating LLM APIs into production workflows.
- Structured problem solving, critical thinking, and a driven, ownership-oriented mindset.
- Effective communication and collaboration in a distributed, cross-functional environment.
Nice to have
- Vertex AI pipelines.
- GPU optimization and cost/performance tuning for training/inference.
- Experience in insurance, automotive, or related computer vision domains.
#LI-MG1
Top Skills
What We Do
Solera is a leading global provider of integrated vehicle lifecycle and fleet management software-as-a-service, data, and services. Through four lines of business – vehicle claims, vehicle repairs, vehicle solutions and fleet solutions – Solera is home to many leading brands in the vehicle lifecycle ecosystem, including Identifix, Audatex, DealerSocket, Omnitracs, eDriving/Mentor, Explore, CAP HPI, Autodata, and others. Solera empowers its customers to succeed in the digital age by providing them with a “one-stop shop” solution that streamlines operations, offers data-driven analytics, and enhances customer engagement, which Solera believes helps customers drive sales, promote customer retention, and improve profit margins. Solera serves over 300,000 global customers and partners in 100+ countries. For more information, visit www.solera.com.
