Data and ML Engineer
Summary
SE3 Labs seeks a Data and ML Engineer in Munich to build AI data pipelines, datasets, and ML workflows using Python/C++ for autonomous systems. This role involves data collection, organization, preparation, and ML model training/evaluation, with a focus on real-world sensor data for defense applications.
Join SE3 Labs as Data and ML Engineer
A great opportunity to take ownership of the real-world data that powers SE3 Labs’ AI, building the collection pipelines, datasets and ML workflows that turn raw sensor recordings into reusable models for autonomous machines.
About SE3
SE3 Labs builds spatial intelligence and autonomy software for unmanned systems. We combine 3D computer vision, state estimation and AI to help autonomous platforms perceive their surroundings, know where they are and operate when GPS and other sensors become unreliable. Defence is a core application of our work today.
We are growing to a team of 100+ people. Join at a stage where you can shape our AI and Computer Vision Team, help build the team and grow your responsibilities as the company expands.
Our founding team’s research has received more than 90,000 citations. You will work closely with technical founders and engineers with deep experience in computer vision and autonomous systems, turning that research depth into systems that work in the field.
About the Role
As a Data and ML Engineer at SE3 Labs, you’ll take ownership of how we collect, organise, prepare and reuse real-world data across the company. You’ll work closely with engineering, hardware and testing teams to coordinate data collection, build shared data stores and pipelines, and establish clean, repeatable processes for preparing datasets. You’ll also develop machine learning workflows for training, fine-tuning and evaluating models, helping turn data collected across projects into reusable assets that support our work.
What You’ll Work On
Data Collection & Coordination: Plan and coordinate real-world data collection with hardware and testing teams, working with sensors and pilots where relevant to capture data for specific project needs.
Data Organisation & Management: Build and maintain a shared data store, ensuring recordings and datasets are organised, categorised, cleaned and easy to find and reuse across projects.
Data Preparation & Labelling: Establish clear, repeatable workflows for preparing and labelling datasets, improving consistency and making data ready for machine learning and evaluation.
Data Pipelines & Processes: Build a pipeline for bringing new data into the shared store, taking ownership of the process from collection through preparation and making it usable across the company.
Use Cases & Data Gaps: Work with engineering teams to understand project requirements, define concrete use cases, identify gaps in existing datasets and plan future data collection campaigns.
ML Training & Fine-Tuning: Develop workflows for training and fine-tuning machine learning models using real-world data, helping turn project-specific experiments into reusable models and assets.
Evaluation & Improvement: Support model evaluation using prepared datasets, assess where additional data is needed and help improve models through better data coverage and preparation.
Cross-Team Collaboration: Take the initiative to coordinate colleagues, establish clear processes and ensure data collection and preparation efforts are aligned across projects rather than duplicated.
Building for Reuse: Develop a shared library of datasets and perception models that engineers across SE3 Labs can use, reducing repeated work and helping accelerate future projects.
Your Profile
You take ownership: You are highly organised, proactive and comfortable taking the lead, coordinating people and tasks, and putting clear processes in place. You follow through and make sure things get done.
You have hands-on ML experience: You have experience applying machine learning to real-world data, including training models using practical datasets. You understand how data quality and preparation affect model performance.
You bring practical data skills: You have experience collecting, cleaning, organising or preparing datasets, ideally from real-world systems or technical projects.
You hold a degree in a relevant field: You have a Master’s degree in Machine Learning, Data Science, Robotics, Computer Science or a related technical discipline, or equivalent practical experience.
You can work with data and code: You are comfortable using Python and/or C++ to work with data and develop ML workflows.
You are comfortable working across teams: You can coordinate with engineers and other colleagues, gather requirements, identify data gaps and turn them into practical collection and preparation plans.
You are hands-on and adaptable: You are happy to work directly with data, learn new tools and processes, and get involved in sensor integration and field data collection. Previous sensor experience is a plus, but not essential.
You communicate clearly: You speak fluent English and can work effectively with colleagues across technical teams.
Especially Valued Bonus Skills
Data Engineering & ML: Experience building data pipelines and workflows for training, fine-tuning and evaluating machine learning models.
Real-World Dataset Experience: Practical experience collecting, cleaning, labelling and preparing datasets from real-world systems, rather than working exclusively with curated or synthetic data.
Robotics & Sensor Data: Experience working with robotics, UAVs or sensor data, particularly where collecting reliable data in real-world environments presents practical challenges.
Initiative & Project Coordination: A track record of taking ownership, coordinating people and projects, and establishing processes that others can adopt and reuse. This could include leadership in university projects, research groups or student organizations.
End-to-End Model Development: Experience taking ML models from dataset creation and preparation through training and evaluation, with an understanding of how to identify data gaps and improve results.
Perks & Benefits
Real Ownership: Participate in SE3’s growth through our employee participation programme
Work Environment to Excel at: Find a high-quality and modern toolset, flat hierarchy and a skilled, driven team which will push the limits together with you
AI-boosted workplace: We empower every employee with best-in-class AI tools and agents, giving you unlimited access to the latest advancements and a true productivity edge
31 Paid Days Off: 30 vacation days plus your birthday off
Well-being Access: Free membership to gyms, yoga, and wellness through EGYM Wellpass
Team Offsites: We go on 2 company retreats per year, our last ones were in Italy and Greece
Mentorship: Work closely with experienced engineers and get paired with a professional mentor to support your growth
Our Process
Intro Call (30 min): Let’s get to know each other
Technical Interview: (45 min): Technical and team level conversation
Coding Exercise (90 Mins): We dive into your experience with Data, Machine Learning, building Data Pipelines, robotics, and real-world debugging
Team Dinner / Lunch: Meet the team and see whether it is a strong fit on both sides.