Applied Scientist – LLM, Geospatial Data & AI Systems

TomTom; Madrid; Híbrido; EUR 65.000 - 90.000; Jornada completa

Ventajas ofrecidas por este puesto de trabajo

Personal development budget

Learning resources access (O’Reilly, L

Paid learning days

Descripción de la vacante

TomTom is seeking a research-focused ML scientist to help design LLM-powered data interfaces within our Navigation SDK team. You will shape retrieval strategies, embeddings for geospatial data and grounding techniques to scale location-aware AI.

Collaborate with product managers and engineers to convert opportunities into rigorous experiments, define meaningful metrics, and push solutions from prototype to production while balancing accuracy, latency and cost.

Formación

• Strong foundations in ML, DL, statistics and optimization.
• Hands-on experience with PyTorch or JAX and Python data stack.
• Experience with LLMs, CV, time-series, graphs or RL.
• Ability to design experiments, define metrics and draw conclusions from data.
• Experience with large-scale datasets and distributed computing (Spark/Databricks, cloud).

Responsabilidades

• Research and design LLM data interfaces and retrieval strategies.
• Develop representations for geospatial data and knowledge graphs.
• Define evaluation benchmarks and metrics for location-grounded tasks.
• Design and train ML models, including LLMs and multi-modal methods.
• Turn opportunities into well-defined scientific problems with metrics.
• Produce production-quality code and collaborate with engineers for deployment.
• Keep up with SOTA in LLMs, retrieval and agentic systems.
• Communicate findings to technical and non-technical audiences; publications encouraged.

Conocimientos

ML fundamentals

Deep learning

Communication skills

Experiment design

Publications track record

Educación

Bachelor/Master/PhD in CS or related quantitative field

Herramientas

PyTorch

JAX

NumPy / pandas / scikit-learn

Spark

Databricks / Cloud ML platforms (Azure/AWS/GCP)

Descripción del empleo

TomTom is seeking a research-focused ML scientist to help design LLM-powered data interfaces within our Navigation SDK team. You will shape retrieval strategies, embeddings for geospatial data and grounding techniques to scale location-aware AI.

Collaborate with product managers and engineers to convert opportunities into rigorous experiments, define meaningful metrics, and push solutions from prototype to production while balancing accuracy, latency and cost.