Senior Software Engineer (ML)

2 years ago

Columbia, MD, USASenior

Responsibilities

Design, implement, integrate, maintain, and deploy software applications and services for scalable analytics and operationalized data science.
Translate business, system, and customer requirements into technical solutions and collaborate on interfaces, data flows, and integration requirements.
Write clean, maintainable, well-documented, and testable code and participate in architecture, design, and code reviews.
Develop unit, integration, system, and automated regression tests and troubleshoot defects, performance issues, deployment problems, and production incidents.
Support continuous integration, continuous delivery, system deployments, operational readiness, and sustainment activities.
Contribute to documentation, technical procedures, engineering standards, Agile planning and estimation, and software performance, reliability, security, and maintainability improvements.
Mentor less-experienced engineers and communicate technical status, risks, dependencies, and recommendations to leadership.

Bachelor’s degree in computer science, software engineering, information technology, or an equivalent combination of education and experience.
Eight years of professional software development experience.
Active TS/SCI clearance with polygraph.
Demonstrated experience developing and delivering production-quality software.
Strong proficiency in at least one of Java, C#, C++, Python, JavaScript, or TypeScript.
Experience with software design principles, object-oriented or functional programming, common development patterns, source-control systems, code reviews, automated testing, and defect tracking.
Ability to analyze requirements, develop well-engineered solutions, troubleshoot complex technical issues, and work collaboratively in a multidisciplinary environment.
Understanding of software development lifecycle processes and Agile development practices.
Preferred experience includes distributed, cloud-based, web-based, embedded, or mission-critical systems; RESTful APIs, microservices, messaging systems, or service-oriented architectures; AWS, Microsoft Azure, or Google Cloud; and Docker, Kubernetes, infrastructure as code, or automated deployment pipelines.

501-1,000 employees