Senior Software Engineer (ML)

Aves Reality
München, Germany
3 days ago

Role details

Contract type
Permanent contract
Employment type
Full-time (> 32 hours)
Working hours
Regular working hours
Languages
English
Experience level
Senior

Job location

München, Germany

Tech stack

Geographic Information Systems
Amazon Web Services (AWS)
Systems Engineering
C++
Nvidia CUDA
Geospatial Intelligence
Python
Machine Learning
Systems Architecture
Transport Layer Security
PyTorch
Deep Learning
Data Pipelines

Job description

Design, implement, and extend key features of our core product, the "AVES Launcher"

  • Develop and optimize pipelines and interfaces for geospatial data, mapping systems, and 3D mesh processing.
  • Design custom model architectures and data pipelines leveraging the latest advancements in geospatial intelligence.
  • Analyze and benchmark deep learning architectures and training strategies (SL, RL, SSL) to maximize real-world performance.
  • Take full end-to-end ownership of features - from concept and implementation to testing, integration, and deployment.
  • Collaborate closely with our CTO on system architecture, feature planning, and technical strategy., * Open and supportive team culture, regular feedback loops, and a motivated team that shares a result driven and success-celebrating spirit.
  • Continuous personal and professional growth through new challenges and responsibility from day one.
  • Startup mentality with long-term prospects: Direct opportunities to contribute and actively shape our company and product - your work will make an impact!

Requirements

Do you have experience in Systems engineering?, 3+ years in SW engineering with a focus on deep learning.

  • Strong proficiency in Python and PyTorch (required); experience with C++/CUDA is a plus.
  • Proven experience developing machine learning solutions from inception to production.
  • You are an independent, creative problem-solver with a proactive mindset.
  • You are comfortable working in an agile, fast-moving startup environment.
  • Experience with AWS/GCP training infrastructure is a plus.
  • Experience with vision-language models or geospatial ML models is a plus.

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