Machine Learning Software Engineer

Vor 7 Tagen

Berlin, Berlin, Deutschland LiveEO GmbH Vollzeit
Build the Market Leader in Satellite Analytics with us at LiveEO

At LiveEO, we combine Space Technology with AI to solve problems here on Earth. LiveEO is applying the latest developments in artificial intelligence to analyse satellite data and is bringing the insights of earth observation data to customers in the enterprise sector. LiveEO's ambitious goal is to monitor 1 billion assets across the globe with its unique SaaS solution until 2030.

We are looking for highly skilled Machine Learning Software Engineers with a focus on Data Engineering and Machine Learning Operations to join our dynamic team. LiveEO leverages satellite imagery and artificial intelligence to provide actionable insights that drive decision-making across various industries. An example is the precise detection of trees and their height in high resolution imagery to protect our customers power grids from tree fall.In the role you will focus on building robust and automated data pipelines that handle terabytes of data. Our pipelines involve a wide-range of topics such as efficient tiling strategies, merging of different data sources and various geospatial data processing challenges. Beyond that you will work closely with our Dev & DataOps expert and use our in-house ML Framework to streamline data transformations and model serving. Memory optimization of our data pipelines and ML Models is a core part of this job.
This is a chance to build a very strong Data Engineering and MLOps profile, working with deep-tech and state-of-the-art orchestration frameworks

Your challenge
  • Build and maintain efficient and reliable pre-processing pipelines to deal with large volumes of satellite imagery and related data.
  • Work with orchestration engines such as Prefect to orchestrate and automate workflows.
  • Design and build training pipelines, including data pre-processing, dataset management, data collection tools and more
  • Refactor, redesign, rebuild existing model implementations.
Your profile
  • Excellent Python programming skills with a strong emphasis on writing clean, efficient, and maintainable code.
  • Experience in designing, building, and maintaining data pipelines, with a strong background in handling large datasets.
  • Willingness to work on the more engineering related side of Machine Learning, e.g. model deployment and data throughput optimisation.
  • Being both a team player and having the ability to work independently.
Nice to have:
  • Experience with MLOps and best practices around model serving for automatic inference and training.
  • Familiarity with orchestration engines like Prefect to manage data & ML workflows efficiently.
  • Experience in setting up CI/CD pipelines.
  • Familiarity with geospatial data processing tools and techniques, such as PostGIS and Cloud Optimized GeoTIFFs (COGs) would be as a plus.
Your Benefits
  • The opportunity to create a product that can improve business processes and lives across the globe.
  • Flexible working hours and hybrid work model - we trust our employees to get their work done while maintaining a healthy work-life balance.
  • We empower employees to drive their own career development, take initiative and have the freedom to be creative and bold.
  • Not an overtime culture - we take care that overtime is done only as a necessity and always offset with time off and rest.
  • Variety of team building opportunities - from jogging groups, team sports, bouldering and picnics.
  • A collaborative and learning environment - frequent internal workshops, knowledge sharing sessions, journal clubs and hackathons.
  • Potential to participate in the employee stock option program.
  • Office located in the center of Berlin Kreuzberg with free fruit, nuts and drinks.
  • Urban Sports membership and BVG subsidy.
About us

LiveEO is a well funded startup founded in 2018 and based in Berlin. Our primary service is modelling risk to our customers' assets and infrastructure from vegetation, ground deformation and change detection. We currently have around 100 employees from all over the world with a variety of backgrounds

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