Software Engineer (multiple openings)
Numerica's Software Engineers excel at developing state-of-the art algorithms and software that solve scientific problems with real-world applications. Working in small innovative teams, our software engineers build solutions that make a difference. Our research endeavors donâ€t end once weâ€ve written a journal or conference paper describing our technology; rather, our work is complete when our technology has been deployed in mission-critical systems and our customers within government and industry are successful. As science fiction writer Arthur Clarke wrote, â€œAny sufficiently advanced technology is indistinguishable from magic.â€ Numerica is seeking talented â€œmagiciansâ€ to join in our mission to expand the boundary of whatâ€s possible. What You Will DoContribute to the direction of a small team with your expertise and ideas;Prototype state-of-the-art software solutions in an agile development environment;Implement high-performance software spanning the spectrum from tactical systems to web applications;Use high-fidelity modeling and simulation environments, innovative analysis tools, and sound analysis techniques to quantify the benefit of our technology;Engage with our customers, to ensure successful outcomes for their mission-critical needs;Work with all aspects of the software development lifecycle;Help your colleagues and customers understand what youâ€re doing and why. Recommended Background and ExperienceA Software Engineer at Numerica should possess a B.S., M.S., or Ph. D. in Computer Science, Applied or Computational Mathematics, Electrical Engineering, Aerospace Engineering, Controls and Dynamical Systems, Statistics and Probability, or a closely related field.
A Software Engineer should have a record of academic excellence, including demonstrated experience in one or more of the following areas: Software engineering: software design, algorithm implementation, and software analysis, testing, and optimization;Machine learning: supervised and unsupervised learning, clustering, and classification;Applied mathematics: differential equations, linear algebra, optimization, statistics, and random processes;Engineering: controls, estimation theory, and digital signal processing.