Machine Learning Engineer
SpaceKnow, Inc.
Praha, Czech Republic
před 14 dny
source : Startupjobs

Full-time :

SpaceKnow provides transparency to global changes and trends by combining the world’s largest collection of satellite imagery with a proprietary artificial intelligence engine.

Our vision is to index the physical world and empower users with near-realtime large-scale analysis to drive decision making.

SpaceKnow has two distinct products : a web-based, on-demand geospatial analytics platform (also available through API), as well as a growing suite of economic index offerings delivered through Bloomberg.

Join a team of passionate Machine Learning Engineers to advance the state of the art in novel machine learning approaches and data science tools for processing satellite images!

You should have a proven track record of creatively solving difficult problems and you should enjoy spending your time writing code and producing results.

Have experience with big data analysis, image processing, deep neural networks and cloud computation is a great plus.

Following qualifications that will make you a perfect candidate :

Software development experience in data manipulation, data mining or prototype development using Python (agile development, software version control, continuous integration, test driven development, pair programming, rapid prototyping)

Data analysis and signal processing skills with an ability to independently prototype machine learning (deep learning) pipelines

Understanding of mathematical modeling, computer vision, statistical analysis, data mining

Skilled in creative, strategic thinking and an ability to propose and deliver simple solutions to complex puzzles

Excellent communication and collaboration skills

Self-motivated and independent

Masters or PhD in computer science, machine learning, data science or signal processing

Joining Spaceknow, you will join a young team of talented and highly motivated people who strive to make an impact on the world but also have fun along the way.

Do not hesitate to send links of your contributions to FOSS projects or of any other relevant work.

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