Data Engineer (Robotics)

TL;DR

Data Engineer (Robotics): Building and optimizing a scalable data collection and processing platform for autonomous driving with an accent on dense robotics data and Data Mesh architecture. Focus on designing efficient ingestion pipelines for sensor data and collaborating with ML teams to ensure system safety.

Location: Hybrid; must be based in or be able to work from the Gothenburg or Stockholm offices

Company

hirify.global transforms road freight using digital, electric, and autonomous technologies to enable sustainability for businesses worldwide.

What you will do

• Develop strategy and architecture for collecting, processing, and leveraging large-scale data.
• Design and implement scalable solutions for the collection of dense robotics data, including raw sensor data and service messages.
• Develop a Data Mesh platform to enable Machine Learning, Validation & Verification, and Systems Engineering teams.
• Collaborate with experts in ML, MLOps, and Perception to build a state-of-the-art safe autonomous driving system.

Requirements

• 5+ years of professional experience in software or data engineering.
• Background in Computer Science, Software Engineering, Mechatronics, or Electronics.
• Strong communication skills to engage effectively with technical and non-technical stakeholders.
• Ability to thrive in a fast-paced startup environment.
• Must be present at the office in Gothenburg or Stockholm as part of the hybrid setup.

Nice to have

• Proficiency in Go or C++ programming languages.
• Experience working with Google Cloud Platform (GCP).
• Knowledge of distributed and event-driven systems.
• Experience with multiple data models, such as PostgreSQL, BigQuery, or Firestore.
• Experience collecting and processing large volumes of sensor data (camera, LiDAR, radar).
• Understanding of machine learning training processes.

Culture & Benefits

• Modern hybrid work setup allowing for partial work-from-home.
• Opportunity to work within a truly diverse, high-performing team.
• Culture driven by sustainability and innovative problem-solving.
• Environment that encourages knowledge sharing and continuous learning.