Versive: Machine Learning Scientist
Seeking a Machine Learning Scientist who will continue to advance our platform for cyber, and apply it to problem spaces beyond cybersecurity, and be directly involved in full-cycle delivery, building quality software, story telling, and interacting cross-functionally across teams.
Location: Seattle, WA
Position: Machine Learning Scientist
We believe it needs to be simpler for enterprises to effectively use AI. Our products strategically combine human expertise with machine learning to deliver results that are better than what either an expert or machine could achieve individually. Our first proof case is in cybersecurity: enabling enterprises to surface high-risk threats that are currently invisible to other approaches. Our approach generates meaningful results, with low false positives, by combining automated modeling of each customer environment with a focus on fundamental adversary behaviors.
Versive is recognized on CB Insights’ prestigious AI 100 list of the most promising, privately-held artificial intelligence companies, as well as on the SINET 16 list of the most innovative cybersecurity companies. The Versive Security Engine won “Best of Interop 2017” for emerging security solutions.
At Versive, we want to cut through the hype and overblown claims surrounding AI and ML and help our customers successfully tackle their biggest challenges. We built our own proprietary machine learning platform on top of open-source distributed computing technologies such as Apache Spark to provide automated and explainable artificial intelligence-driven solutions to our customers. As a Machine Learning Scientist, you will continue to advance our platform for cyber, and apply it to problem spaces beyond cybersecurity
What you will do:
- Full-cycle delivery: Understand the problem; generate ideas; prove the idea works; build the solution as production software; assist with deployment to customers.
- Machine Learning: Use your expertise in statistics and machine learning to analyze massive, messy real-world data sets and then create solutions that are general, repeatable, and automated.
- Quality Software: Make it easy to get high quality, automated, results --- without expert intervention. Build scalable products and reusable libraries in Python, Scala, and C++, taking advantage of Spark, Hadoop, and other tool stacks as appropriate.
- Story telling: Present findings (e.g., experiments, forecasts, cost-benefit analysis) and business recommendations to stakeholders, internal and external, with quantitative information.
- Interact cross-functionally: Work with people across teams to find creative solutions and deliver them.
What you will bring:
- Ph.D. in Computer Science, Mathematics, Electrical Engineering, Statistics or related field, with a focus on Machine Learning, and relevant work or internship experience
- M.S. AND 3 + years of applied machine learning at scale preferably using Python, Scala, Java, or C++
- CS fundamentals: You have earned at least a B.S. in Computer Science, Computer Engineering, or related degree and you have a strong ethos of continuous learning.
- Relevant Experience: You have a proven track record of delivering machine learning products that solve real customer problems.
- Design and execution: You are comfortable with a wide set of machine learning approaches and designing the features and data processing to actually make them work.