Posted in General Business 5 days ago.
Location: Arlington, Virginia
The Two Six Technologies Data Science Team applies expertise in machine learning, data visualization, statistics, and computational architectures to solve hard research challenges in AI security & privacy, synthetic biology, cyber security, computational social science, code analysis, biometrics, and other areas. We have built systems that summarize source code, predict protein stability, visualize graphs with millions of nodes, and detect stealthy denial-of-service attacks. Our team values creativity, initiative, collaboration, and diversity. We strive for a fun and collegial atmosphere that encourages intellectual cross pollination and professional growth. We are passionate about empowering our customer's missions and enjoy working together at the leading edge of technology!
As a Senior Machine Learning Engineer , you will research novel machine learning methods, apply them to challenging problem domains, and present empirical research results. You will develop, apply, and evaluate state-of-the-art natural language processing techniques to solve complex cyber problems. You may contribute to technical proposals in new research areas. You will work collaboratively on a multidisciplinary team alongside experts in deep learning, cybersecurity, signal processing, and software development with clients that include DARPA and other government agencies.
Two Six Technologies is an Equal Opportunity Employer. All qualified applicants will receive consideration for employment at Two Six Technologies without regard to race, color, religion, national origin, sex, age, physical and mental disability, sexual orientation, gender identity or expression, genetic information, veteran, marital, pregnancy or citizenship status; or any other status prohibited by applicable national, federal, state or local law.
If you are interested in applying for employment with Two Six Technologies and require an accommodation, please contact Human Resources at Two Six Technologies by calling 703-543-9662 or sending an email to email@example.com . Information provided will be kept confidential and used only to the extent required to provide needed reasonable accommodations.