Senior Full-Stack Machine Learning Engineer- OPTIX

GA-CCRi maintains and deploys production systems for users across the Intelligence Community, Department of Defense, and commercial industry. We build and develop best-in-class all domain and globally focused situational awareness capabilities, including THRESHER and DRAGONSPELL, that process petabytes of data from numerous streaming data sources in near real time. Our systems apply state-of-the-art algorithms and machine learning techniques to extract features and fuse data from multiple phenomenologies to form a rich live view of objects in the sky, on the sea, and on the ground. These analytics are designed to determine not just where something is, but what it is, where it's been and what it's doing. All of this "data to knowledge" is made available to end users in our own browser-based application for visualization, analysis, and understanding. We always want to do more, and that's where you come in!

As a member of the GA-CCRi core product team, you'll be at the forefront of innovation, shaping the future of situational awareness capabilities for our customers. Imagine using cutting-edge technology to process petabytes of data and extract features in near real time, all while providing a rich, live view of objects on land, sea, and sky. With your skills and expertise, you'll be instrumental in taking our systems to the next level, giving end-users the power to see beyond the data and truly understand the world around them. Are you ready to join us on this exciting journey?

Positions available in: Charlottesville, VA

Duties and Responsibilities

• Design, develop and program methods, processes and systems to consolidate and analyze unstructured, diverse 'big data' sources to generate actionable insights and solutions for client services and product enhancement.
• Develop, refine, deploy, and support statistical and machine learning models utilizing state of the art approaches.
• Interpret and communicate insights and findings from analysis and experiments to product, service, and business managers.
• Recommend solutions to a variety of highly complex technical and procedure issues.
• Create and utilize highly complex algorithms and approaches, clean and synthesize training/test data, create/run simulations, and perform analysis of alternatives to best meet stakeholder requirements.
• Lead in the identification of opportunities for product and customer process improvement using statistical and machine learning models to improve the effectiveness of different courses of action.
• Develop and deploy data visualization in order to communicate highly complex concepts and data in a simple, actionable manner.
• Interact with product and service teams to identify questions and issues for data analysis and experiments.
• Evaluate the integration of solutions within the overall data science environment; and ensure that appropriate documentation, testing, maintenance, and updates are completed.
• Document findings and make technical presentations to business stakeholders as required.
• Create proposals, cost estimates, and whitepapers suitable for publication.
• Represents the organization as a primary contact with internal and external representatives.
• May function in an advisory or leadership role and provide direction and guidance to less experienced staff.
• Maintain the strict confidentiality of sensitive information.
• Perform other duties as assigned or required.
• Responsible for observing all laws, regulations and other applicable obligations wherever and whenever business is conducted on behalf of the Company.
• Expected to work in a safe manner in accordance with established operating procedures and practices.
• As a senior machine learning engineer, you will be expected to balance technical responsibilities (design and development) with team responsibilities (technical planning, roadmaps, ticket creation and delegation, mentorship). You’ll likely conduct demos and give presentations, and will be expected to contribute to the data science culture and ecosystem at CCRi through opportunities like design reviews and shared learning opportunities.

We recognize and appreciate the value and contributions of individuals with diverse backgrounds and experiences and welcome all qualified individuals to apply.

Requirements

Essential Qualifications

• Typically requires a bachelor's degree, master's degree or PhD in data science, applied mathematics, statistics, computer science, or related technical/quantitative discipline from an accredited institution and progressive data science experience as follows; nine or more years of experience with a bachelor's degree, seven or more years of experience with a master's degree, or four or more years with a PhD.