ML Data Engineer (m/f/d) - Sensor Data & Pipelines

Autonomous Teaming

München

Vor Ort

EUR 90.000 - 140.000

Vollzeit

vor 34 Stunden
Sei unter den ersten Bewerbenden
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Benefits dieser Stelle

International team
Career growth
Team events
Continuous development

Zusammenfassung

Autonomous Teaming in Munich seeks a senior ML data engineer to own the data foundation for perception systems end-to-end, shaping data collection, labeling, and pipeline architecture.

You will partner with ML, perception, and robotics teams to turn raw sensor data into production-grade datasets, enabling metrics-driven improvements and scalable tooling.

Qualifikationen

  • 5+ years in Python and data processing frameworks (Pandas, NumPy).
  • Proven ETL/ELT pipelines for large-scale video and sensor datasets.
  • Experience with ML data lifecycle: ingestion, labeling, QA, and reproducibility.
  • Strong knowledge of object detection pipelines and evaluation metrics.
  • Experience with data annotation platforms (CVAT, Label Studio) and QA workflows.

Aufgaben

  • Architect and own scalable pipelines for ingesting large volumes of time-series sensor data (RGB, IR, depth, IMU).
  • Drive dataset strategy for object detection ensuring quality and diversity at scale.
  • Design active learning loops linking model performance to data selection.
  • Own labeling workflows, tooling decisions, QA, and annotation coordination.
  • Collaborate with AI Engineers to diagnose weaknesses and translate findings into dataset strategy.
  • Plan data collection campaigns to fill data gaps with high-value real-world data.
  • Build internal tools/dashboards for dataset quality and performance insights.

Kenntnisse

Python
Data processing
ETL/ELT pipelines
Data orchestration
Object detection pipelines
Active learning
Data annotation platforms
English (fluent)

Tools

Detectron2
MMDetection
COCO format
CVAT
Label Studio
ROS
Docker

Jobbeschreibung

What we offer
  • Work in an international, agile team creating the future of autonomous systems
  • Grow your career in a expanding and ambitious engineering team
  • Build innovative products using state-of-the-art technologies in AI, robotics, and autonomy
  • Benefit from a steep learning curve and continuous development
  • Enjoy team events and a strong, collaborative culture
Your mission

This role owns the data foundation of our perception systems end-to-end — the layer that directly determines model performance in real-world environments. You'll set the technical direction for how we collect, curate, and continuously improve the datasets behind object detection, working as a senior technical partner to ML, perception, and robotics teams — turning raw, messy sensor data into reliable, production-grade systems at scale.

You will take full ownership of the ML data lifecycle — from architecture decisions on ingestion and pipelines, through labeling strategy and QA, to driving continuous, metrics-informed dataset improvement — and will be expected to bring judgment and prior experience to how this is done, not just execute a defined process.

What You'll Do
  • Architect and own scalable pipelines for ingesting, organizing, and preprocessing large volumes of time-series camera and multi-sensor data (RGB, IR, thermal, depth, IMU)
  • Drive the strategy behind our object detection datasets, ensuring quality, diversity, and statistical representativeness at scale
  • Design and operate active learning loops that connect model performance directly to data selection and improvement priorities
  • Own labeling workflows end-to-end — tooling decisions, QA methodology, consistency standards, and coordination of annotation efforts
  • Partner closely with AI Engineers to diagnose model weaknesses, bias, and drift, and translate findings into concrete dataset strategy
  • Plan and lead data collection campaigns (field recordings, drone/video capture) to close gaps with high-value real-world data
  • Build internal tools and dashboards that give the org visibility into dataset quality, distribution, and performance gaps
Your profile
  • 5+ years of hands-on experience in Python and data processing frameworks (Pandas, NumPy, vectorized operations, multiprocessing)
  • Proven track record building and owning ETL/ELT pipelines for large-scale video and sensor datasets in production
  • Deep experience with data orchestration and lifecycle management for ML/computer vision workflows, including dataset versioning and reproducibility
  • Strong command of object detection pipelines (Detectron2, MMDetection, COCO format, bounding-box standards)
  • Demonstrated experience designing active learning, uncertainty sampling, or semi-supervised dataset workflows
  • Deep familiarity with data annotation platforms (CVAT, Label Studio) and building automated QA/consistency checks
  • Strong grasp of evaluation metrics for object detection (IoU, mAP, precision-recall curves, class-wise metrics)
  • Comfortable owning decisions around databases (SQL/NoSQL), file systems, and large-scale image, video, and sensor dataset management
  • Track record of working cross-functionally and influencing perception, deployment, robotics, and data infrastructure teams
  • Fluent in English; German and/or French are a plus
Nice to have
  • Experience with cloud storage and MLOps tools (AWS S3, MinIO, ClearML, MLFlow, Weights & Biases).
  • Familiarity with ROS / robotics data formats (bag files, TF trees, sensor_msgs), Docker, or embedded ML workflows.
  • Prior work with robotics, drones, or multi-sensor perception systems, including IR, LiDAR, radar, or audio datasets.
What else
  • Outside-the-box creativity with a blend of conceptual and systematic design thinking.
  • High intrinsic motivation, attention to detail, and strong problem-solving mindset.
  • Structured, methodical, and reliable execution, even under uncertainty.
  • Humble, collaborative, and mission-driven — values collective success over ego.
  • High ethical standards and disciplined work ethic.
  • Extra-curricular achievements, leadership, or unique projects are a plus.
  • NATO-aligned nationality or close ally citizenship is required.
Why us?

Join us to shape the future of AI-driven defense!

About Us

The world is changing. Exponential technologies are enabling new types of security threats. ATS is committed to staying ahead by building nimble, scalable, and cost-effective defences. We are looking for passionate team members who are eager to create exceptional products, safeguard our freedom, and strengthen the resilience of democracies.

Who we are:

Autonomous Teaming is a defence-tech start-up specializing in machine vision solutions. Driven by cutting-edge innovation, our team works on next-generation technologies designed to meet rapidly evolving security challenges.

What we do:

We develop systems that enable computers and sensors to operate as coordinated teams, collaborating in real time to counter AI-powered asymmetric threats at scale — including drone swarms and other UXVs. Our mission is to build resilient, intelligent defence capabilities that perform reliably in the most demanding environments.

How we work:

We value close, in-person collaboration as the foundation for building complex, high-impact technology, while maintaining flexibility aligned to role and team needs. Our culture is built on ownership, responsibility, and trust — with a shared commitment to growing and building together.

Where we are:

Based in Munich, Berlin, and Toulouse, we are expanding rapidly across Europe with plans to open additional office hubs.

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