Principal Machine Learning Scientist at STR

Arlington, Virginia, United States -

Full Time

Start Date

Immediate

Expiry Date

19 Jan, 26

Salary

0.0

Posted On

22 Oct, 25

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Deep Learning, Python, AWS, Data Analysis, Neural Networks, Generative AI, Reinforcement Learning, Database Management, DevOps, CI/CD, Mathematics, Multimodal Data Fusion, Software Optimization, Team Leadership, Research Collaboration

Industry

technology;Information and Internet

Description

About the Team STR’s Intelligence Division researches, develops, and transitions advanced analytics and machine learning-based solutions to solve challenging problems related to national security. Our team consists of passionate and motivated engineers with advanced degrees in engineering, computer science, mathematics, and data science, who are seeking opportunities to use their deep technical knowledge and creativity to tackle some of the hardest problems that our customers face. Our projects span multiple different data modalities and incorporate advanced algorithms, deep learning, and statistical techniques to uncover patterns in social media, structured and unstructured text, time series, geospatial, and imagery data, and must operate under challenging constraints not typically found in the commercial world. The tools and technologies we develop have real world impact and US Government analysts use them to extract and enrich intelligence information around the globe. The Role: We are seeking a highly motivated and experienced Lead Machine Learning Scientist to join our dynamic team. The ideal candidate will have a strong background in machine learning, deep learning, and a proven track record in developing innovative solutions for complex problems. This role requires a deep understanding of mathematical concepts, proficiency in programming languages such as Python, and experience in leading research projects. Lead Machine Learning Scientist will work closely with cross-functional teams to design, develop, and implement machine learning models that drive impactful results in various national security related domains. What you will do: Lead the development of machine learning and deep learning algorithms for large-scale multimodal data fusion problems Deep understanding of Generative AI (GenAI) models and reinforcement learning models to address specific business challenges Lead a team of research scientists and software engineers, guiding project direction and ensuring successful project delivery Collaborate with other research scientists, software engineers, and mission partners to create robust solutions that leverage state-of-the-art deep learning and advanced data analysis techniques Work with large data sets in a parallel computing environment, utilizing tools such as AWS services (EC2, S3, etc.) for data storage and processing Stay up-to-date with the latest advancements in machine learning and artificial intelligence, and contribute to the development of novel algorithms and techniques Design and implement neural network architectures, including transformer-based architectures and autoencoders Refactor and optimize existing software for improved performance and scalability Who you are: Active Top Secret security clearance for which U.S. citizenship is needed by U.S. Government PhD, MS, or BS in Computer Science, EE, Physics, Mathematics, or a related field with 5-10+ years of relevant experience depending on your degree Proven experience in developing bespoke machine learning algorithms, particularly in high-dimensional multivariate complex-valued functions. Strong proficiency in Python, with expertise in libraries such as PyTorch, TensorFlow. Usage experience with cloud computing platforms, preferably AWS Experience in database management, including SQL and NoSQL databases. Excellent understanding of mathematical concepts, including linear algebra, graph theory, and algebraic geometry. Knowledge of DevOps practices and CI/CD pipelines STR is a growing technology company with locations near Boston, MA, Arlington, VA, near Dayton, OH, Melbourne, FL, and Carlsbad, CA. We specialize in advanced research and development for defense, intelligence, and national security in: cyber; next generation sensors, radar, sonar, communications, and electronic warfare; and artificial intelligence algorithms and analytics to make sense of the complexity that is exploding around us. STR is committed to creating a collaborative learning environment that supports deep technical understanding and recognizes the contributions and achievements of all team members. Our work is challenging, and we go home at night knowing that we pushed the envelope of technology and made the world safer. STR is not just any company. Our people, culture, and attitude along with their unique set of skills, experiences, and perspectives put us on a trajectory to change the world. We can't do it alone, though - we need fellow trailblazers. If you are one, join our team and help to keep our society safe! Visit us at www.str.us for more info. STR is an equal opportunity employer. We are fully dedicated to hiring the most qualified candidate regardless of race, color, religion, sex (including gender identity, sexual orientation and pregnancy), marital status, national origin, age, veteran status, disability, genetic information or any other characteristic protected by federal, state or local laws. If you need a reasonable accommodation for any portion of the employment process, email us at appassist@str.us and provide your contact info. Pursuant to applicable federal law and regulations, positions at STR require employees to obtain national security clearances and satisfy the requirements for compliance with export control and other applicable laws.

Responsibilities

Lead the development of machine learning and deep learning algorithms for large-scale multimodal data fusion problems. Collaborate with cross-functional teams to create robust solutions that leverage advanced data analysis techniques.