The Machine Learning Engineer will develop, deliver, and operate AI-driven components for vehicle claims using computer vision and scalable ML pipelines on GCP, deploying services and ensuring performance optimization.
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
BigQuery
Cloud Run
Dataflow
Docker
Fastapi
GCP
Gke
Grafana
Kubernetes
Python
PyTorch
Streamlit
TensorFlow
Vertex Ai
Similar Jobs
Healthtech • Internet of Things • Hospitality • Telehealth
The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.
Top Skills:
AIMachine Learning
Artificial Intelligence • Cloud • Sales • Security • Software • Cybersecurity • Data Privacy
Solution Architects at SailPoint gather customer requirements, educate clients on product architecture, assist in implementation, and build creative solutions, becoming trusted advisors over time.
Top Skills:
AdAngularAWSAzureBeanshellCSSGCPHTMLJavaJavaScriptLdapMssqlMySQLNode.jsOracleReactSpml/SoapSybaseTypescriptXML
Artificial Intelligence • Cloud • Sales • Security • Software • Cybersecurity • Data Privacy
Lead the installation, integration, and deployment of SailPoint IdentityIQ in client environments, providing post-implementation support and training.
Top Skills:
AdBeanshellHTMLJavaJavaScriptJspLdapMssqlMySQLOracleServletsSoapSpmlSQLSybaseXML
What you need to know about the Colorado Tech Scene
With a business-friendly climate and research universities like CU Boulder and Colorado State, Colorado has made a name for itself as a startup ecosystem. The state boasts a skilled workforce and high quality of life thanks to its affordable housing, vibrant cultural scene and unparalleled opportunities for outdoor recreation. Colorado is also home to the National Renewable Energy Laboratory, helping cement its status as a hub for renewable energy innovation.
Key Facts About Colorado Tech
- Number of Tech Workers: 260,000; 8.5% of overall workforce (2024 CompTIA survey)
- Major Tech Employers: Lockheed Martin, Century Link, Comcast, BAE Systems, Level 3
- Key Industries: Software, artificial intelligence, aerospace, e-commerce, fintech, healthtech
- Funding Landscape: $4.9 billion in VC funding in 2024 (Pitchbook)
- Notable Investors: Access Venture Partners, Ridgeline Ventures, Techstars, Blackhorn Ventures
- Research Centers and Universities: Colorado School of Mines, University of Colorado Boulder, University of Denver, Colorado State University, Mesa Laboratory, Space Science Institute, National Center for Atmospheric Research, National Renewable Energy Laboratory, Gottlieb Institute
