Key Skills
Job Description
We’re looking for a Software Engineer to join our team and help us build a production-ready AI/data product for TomTom. The work is covering everything from new feature development to infrastructure, and data Engineering.
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Build AI systems: Design, develop and maintain production AI solutions, including LLM-based applications, retrieval-augmented generation (RAG) pipelines, agentic workflows and ML model services.
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Productionize models: Take models and prototypes from applied scientists and turn them into robust, low-latency, cost-efficient services that scale to global traffic.
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Evaluation and quality: Define and automate evaluation frameworks, benchmarks and guardrails that measure accuracy, safety, latency and cost, and monitor models once they're in production.
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Data and pipelines: Build and optimize data pipelines for training, fine-tuning, embedding and inference, making sure data is high quality, traceable and handled in line with privacy requirements.
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MLOps and infrastructure: Implement CI/CD for ML, model versioning, experiment tracking and observability on cloud platforms.
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Cross-functional collaboration: Work with product, engineering and science stakeholders to understand requirements, weigh trade-offs and deliver AI solutions that meet customer needs.
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Continuous improvement: Keep up with the fast-moving AI ecosystem, evaluate new models, tools and techniques, and share what you learn with the wider engineering community.
- Bachelor's degree in Computer Science, Engineering, AI/ML or a related field, or equivalent professional experience.
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Strong proficiency in one or more high-level programming languages such as C++, Java, Python, or similar languages.
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Hands-on experience with LLMs and their ecosystem: prompt engineering, RAG, embeddings and vector databases, tool use and agent frameworks, and fine-tuning is preferred.
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Solid understanding of software architecture, API design, design patterns and best practices for maintainable, scalable systems.
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Experience with cloud service providers (e.g., Azure, AWS, GCP), containerization (Docker, Kubernetes) and CI/CD tools.
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Knowledge of version control systems, preferably Git.
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Excellent problem-solving and communication skills, with the ability to work effectively in a cross-functional team.
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Experience with ML frameworks and libraries such as PyTorch, TensorFlow or Hugging Face is preferred.
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Familiarity with MLOps practices and tools (e.g., MLflow, experiment tracking, model monitoring) is preferred.
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Experience with geospatial, mapping or location data is a plus, but not required.
Core Responsibilities
Design, develop, and maintain production-ready AI solutions including LLM applications, RAG pipelines, and agentic workflows. Collaborate with cross-functional teams to productionize models while ensuring scalability, performance, and data quality.
Requirements
Requires a bachelor's degree in Computer Science, Engineering, or a related field and strong proficiency in programming languages like Python, C++, or Java. Candidates should have hands-on experience with LLMs, cloud platforms, and MLOps practices.
About TomTom
Industry: IT Services and IT Consulting
Company size: 1,001-5,000 employees
Billions of data points. Millions of sources. Thousands of communities. We are the mapmaker bringing it all together to build the world’s smartest map. TomTom Orbis Maps are the new standard in mapmaking, co-created with the biggest names in tech. It’s a future-proof mapping platform set to drive innovation at a faster pace and on a bigger scale than ever before. Together with our world-leading maps, we provide location data and tech to drivers, carmakers, businesses and developers. Our maps, routing, real-time traffic, APIs and SDKs empower the dreamers and doers to keep the world moving. Headquartered in Amsterdam, TomTom is a global team of 3,700 people. We’ve been shaping the future of mobility for over 30 years – and our journey is just getting started.