Applied Scientist: AI & Geospatial R&D (Hybrid)

TomTom; Madrid; Hybrid; EUR 85,000 - 125,000; Full time

Benefits offered by this job

Personal development budget

Paid learning resources (O’Reilly, LIn

Enhanced parental leave

Flexible work: office + home

Home office setup budget

Work abroad days

Generous holiday plan

Annual Hackathon & DevDays

Job summary

TomTom is seeking an ML-focused researcher for its Navigation SDK team. You will design how LLMs access geospatial data, develop embeddings and knowledge graphs, and build benchmarks for factuality.

You will collaborate with product managers, write production-grade code, publish findings where relevant, and help push state-of-the-art in location-aware AI. This hybrid role offers learning budgets and international collaboration.

Qualifications

• Strong foundations in machine learning, deep learning, statistics and optimization.
• Experience with PyTorch or JAX and Python data stack.
• Experience with LLMs, generative AI, CV, time-series, graphs or RL.
• Ability to design experiments, define metrics and derive conclusions.
• Experience with large-scale datasets and distributed computing (Spark/Databricks/Azure/AWS/GCP).
• Ability to write clean, maintainable production code and collaborate with engineers.
• Excellent communication skills; ability to explain complex ideas to diverse audiences.
• Publications at top venues is a plus, geospatial/mobility data is a plus.

Responsibilities

• Research and design how LLMs access and reason over TomTom data.
• Develop embeddings and knowledge graphs for geospatial entities.
• Define benchmarks and metrics for factuality and accuracy.
• Design and train ML models across domains (LLMs, CV, time-series, graphs).
• Collaborate with product managers to frame problems with measurable success.
• Write production-quality code with AI and software engineers.
• Keep up with state-of-the-art LLMs and adapt techniques.
• Share findings with technical and non-technical audiences; contribute to publications.

Skills

ML fundamentals

PyTorch/JAX

Python stack

LLMs & GenAI

Distributed computing

Experiment design

Geospatial data

Code quality

Publications

System design

Education

Bachelor/Master/PhD in a quantitative field

Tools

PyTorch

JAX

Spark

Databricks

Azure

AWS

GCP

NumPy

Pandas

Scikit-learn

Job description

TomTom is seeking an ML-focused researcher for its Navigation SDK team. You will design how LLMs access geospatial data, develop embeddings and knowledge graphs, and build benchmarks for factuality.

You will collaborate with product managers, write production-grade code, publish findings where relevant, and help push state-of-the-art in location-aware AI. This hybrid role offers learning budgets and international collaboration.