Senior Applied Scientist - Graph Optimization & Trace Alignment

Jobtailor; Amsterdam; On-site; EUR 70,000 - 100,000; Full time

Job summary

Jobtailor in Amsterdam, Netherlands, seeks a Software Engineer to design and implement scalable algorithms for processing large-scale vehicle trace data and to build the lane graph. You will combine deterministic and learned methods, architect high-performance solutions, and collaborate cross-functionally to integrate trace-processing models.

The role requires a Master’s degree and 3–4 years of experience, with strong Python skills, C++ as a plus, and proficiency in Docker, Azure, and

Qualifications

• Master’s degree in computer science, robotics, applied mathematics, engineering, or a related field.
• Software Engineer with at least 3-4 years of professional experience.
• Strong software engineering skills, particularly Python.
• C++ experience for performance‑critical solver and geometry code is a plus.
• 3-4 years of hands‑on experience with optimization‑based estimation.
• Demonstrated experience processing large-scale vehicle trace or trajectory data.
• SLAM and mapping knowledge.
• Working knowledge of modern ML applied to geometric or graph problems.
• Experience with cloud computing platforms such as Azure and Databricks.
• Proficient in deploying applications using Docker containers.
• Ability to think end‑to‑end and deliver high‑quality solutions.

Responsibilities

• Design and implement scalable algorithms for processing large-scale vehicle traces.
• Build and optimize the lane graph itself.
• Combine deterministic and learned methods deliberately.
• Architect high-performance implementations of these algorithms.
• Collaborate with cross-functional teams to integrate trace‑processing and lane‑graph models.
• Stay current with the state of the art in trace‑based mapping.
• Deploy solutions using Docker containers on cloud platforms.

Skills

Python

C++

Optimization

SLAM

Geometric ML

Trajectory data

Cloud computing

Docker

Python tooling

Education

Master's degree in computer science / robotics / applied mathematics / engineering

Tools

Docker

Azure

Databricks

Job description

Responsibilities

• Design and implement scalable algorithms that align, filter, and aggregate large-scale crowd-sourced vehicle traces
• Build and optimize the lane graph itself
• Combine deterministic and learned methods deliberately
• Architect high-performance implementations of these algorithms
• Collaborate with cross-functional teams to integrate trace‑processing and lane‑graph models
• Stay current with the state of the art in trace‑based mapping
• Deploy solutions using Docker containers on cloud platforms

Requirements

• Master’s degree in computer science, robotics, applied mathematics, Engineering, or a related field
• Software Engineer with at least 3-4 years of professional experience
• Strong software engineering skills, particularly Python
• C++ experience for performance‑critical solver and geometry code is a plus
• 3-4 years of hands‑on experience with optimization‑based estimation
• Demonstrated experience processing large-scale vehicle trace or trajectory data
• SLAM and mapping knowledge
• Working knowledge of modern ML applied to geometric or graph problems
• Experience with cloud computing platforms such as Azure and Databricks
• Proficient in deploying applications using Docker containers
• Ability to think end‑to‑end and deliver high‑quality solutions

Expertise in designing and implementing scalable algorithms for processing large-scale vehicle trace data, with strong proficiency in Python and experience in deploying applications using Docker on cloud platforms. Knowledge of SLAM, mapping, and modern machine learning techniques applied to geometric or graph problems is essential.