AI Engineer
Confirmed on the employer's own hiring board on Oct 15, 2026. First seen by Alion on Jul 27, 2026. TomTom scores B on the Alion truth index.
We're looking for a skilled Software Engineer to join our team and help us build a production-ready AI product for TomTom. The work is full-stack, covering everything from new feature development to infrastructure and client-side integration.
What you'll do
New Feature Development: Design, implement, and deploy new features using Python to enhance our core AI functionalities.
DevOps and MLOps: Contribute to the development and maintenance of our CI/CD pipelines and MLOps infrastructure. This includes automating model training, deployment, and monitoring processes to ensure product resilience and scalability.
In-house Evaluation System: Develop and improve our internal evaluation system to accurately measure model performance, track key metrics, and ensure data integrity.
Integration and Deployment: Manage the integration of our AI solution into client environments.
AI Model Improvement: Work with our existing models to enhance their performance and efficiency. This will include tasks like fine-tuning large language models and applying advanced prompt engineering techniques.
R&D Contributions: Participate in short-term research and development projects to explore new technologies and approaches that can give our product a competitive edge.
Product Hardening: Take ownership of tasks focused on making the product production-ready, including improving reliability, enhancing performance, and implementing robust error handling and monitoring.
What experience you'll need
- Python Development: Building new features and improving existing ones.
DevOps and MLOps: Managing CI/CD pipelines and automating model deployment.
Client Integration: Working on client-side integration
Evaluation Systems: Developing in-house systems to monitor and measure model performance.
AI/ML Techniques: Applying fine-tuning and prompt engineering to enhance model performance.
Production Readiness: Making the product resilient and ready for production, including performance optimization and robust error handling.