Machine Learning Engineer, Turion Space

• Bachelor's or Master's degree in Data Science, Machine Learning, or related technical field, or have 4+ years of relevant professional experience
• Strong programming skills in Python
• Strong experience with one or more of the following: Pytorch, Tensorflow, Jax
• Strong understanding of linear algebra, calculus, statistics, and machine learning
• Experience in developing advanced machine learning applications
• Experience with data analysis, data engineering, and data exploration techniques
• Excellent problem-solving, critical thinking skills, and strong engineering fundamentals
• Be able to effectively communicate complex topics and algorithms related to your work
• Strong oral and written communication skills
• Experience with Linux and shell command-line tools
• Must be willing to travel for participation in cross-company collaboration
• Must be able to work extended hours and weekends as needed on rare occasions
• Must be able to obtain a Secret and/or a TS/SCI clearance

Desirable

• The Machine Learning Team concentrates on developing and implementing novel machine learning algorithms for solving trailblazing problems in the developing new space economy
• These include but are not limited to, Computer Vision, Edge Processing, Data Fusion, and probabilistic statistical modeling
• As a Machine Learning Engineer, you will innovate upon existing capabilities, assimilate current research, implement state-of-the-art algorithms, productionize models, develop MLOps solutions, and work with end-users to integrate solutions
• Reporting To: Jackson Parker
• Design, develop, and validate algorithmic solutions which are highly reliable and scalable
• Research and identify useful algorithms for challenging space-based applications
• Optimize the runtime performance of existing implementations
• Interface with end-users and partners in Colorado Springs' collaborative environments
• Integrate current and future machine learning solutions into production pipelines
• Contribute to team discussions, providing insight and feedback to collectively drive innovation across several related projects

• Expected start date: January 2025
• Applied
• Review
• Technical Interview
• Take Home Interview
• Final Interview
• Hired