Senior Software Developer (MLOps)

In a world of possibilities, pursue one with endless opportunities. Imagine Next!At Parsons, you can imagine a career where you thrive, work with exceptional people, and be yourself. Guided by our leadership vision of valuing people, embracing agility, and fostering growth, we cultivate an innovative culture that empowers you to achieve your full potential. Unleash your talent and redefine what’s possible.Job DescriptionParsons is seeking a Senior Software Developer to support our cutting-edge Drone Armor counter-unmanned aerial systems (C-UAS) program. The Senior Developer will design and implement logical, functional software code across multiple programming languages, make informed technology choices for different environments, rapidly diagnose and correct complex software issues in mission-critical systems, and help design, deploy, and operate machine learning capabilities using modern MLOps practices.What You'll Be DoingAdvanced Software Design & DevelopmentCreate logical and functional software code in a variety of programming languages to support Drone Armor capabilitiesLead the design and implementation of software components, services, and interfaces based on system and mission requirementsEnsure solutions are robust, secure, maintainable, and aligned with program architecture and coding standardsDesign and implement data and model-serving services that integrate machine learning components into operational C-UAS workflowsMLOps, ML Integration & Lifecycle ManagementCollaborate with data scientists and ML engineers to productionize models, including feature pipelines, inference services, and monitoringImplement and maintain end-to-end MLOps workflows, including data ingestion, model training, validation, versioning, deployment, and rollbackIntegrate ML pipelines into CI/CD processes to enable automated testing, packaging, and deployment of models and ML-enabled servicesEstablish observability for ML systems (data drift, model performance, latency, accuracy) and support continuous model improvementEnsure ML systems meet mission-critical requirements for reliability, explainability, security, and compliance in DoD/defense environmentsTechnology Evaluation & Trade-OffsUnderstand and articulate the benefits and risks associated with different coding languages and frameworks in various functional environmentsRecommend appropriate languages, tools, and design patterns based on performance, security, maintainability, and integration needsEvaluate and recommend ML frameworks, data processing tools, and MLOps platforms (e.g., experiment tracking, model registries, feature stores)Provide technical guidance to developers on language and framework selection, coding practices, architectural decisions, and ML/MLOps integration strategiesTroubleshooting, Debugging & QualityReact to software problems quickly and effectively, correcting code and related configurations as necessaryDebug complex issues across multiple layers (application, service, interface, data) and environments (development, integration, field)Diagnose and resolve issues specific to ML systems, including model-serving performance, data quality, and pipeline failuresSupport and refine unit, integration, system-level, and ML-specific tests (e.g., data validation, model performance checks) to validate functionality and prevent regressionsLeadership & CollaborationServe as a senior technical resource within the development team, mentoring junior and mid-level developersCoach team members on best practices for integrating ML components and MLOps into existing software architecturesCollaborate with systems engineers, test engineers, data scientists, ML engineers, and field personnel to resolve issues and improve system performanceContribute to technical reviews, design walkthroughs, and continuous improvement of development and MLOps practicesWhat Required Skills You'll BringEducationBachelor’s degree in Computer Science, Electronics Engineering, or other engineering or technical discipline is required with 5 years of experience OR8 years of relevant software development experience may be substituted for educationExperienceExperience creating logical and functional software code in multiple programming languagesExperience understanding and clearly articulating the benefits and risks of different coding languages in different functional environmentsExperience reacting to software problems and correcting programs as necessary in complex or mission-critical systemsExperience deploying, operating, or supporting machine learning models in production environments (MLOps), including monitoring and maintaining ML-enabled servicesTechnical CompetenciesProficiency in one or more modern programming languages (e.g., Python, C++, Java, C#, Go, or similar), with working knowledge of othersStrong grasp of software engineering best practices, including design patterns, code reviews, version control, and CI/CD workflowsDemonstrated ability to troubleshoot and resolve complex software defects efficientlyExperience integrating ML workflows into software systems (e.g., REST/gRPC model services, batch inference, streaming pipelines)Familiarity with MLOps concepts and tools such as:CI/CD for ML (e.g., automated training and deployment pipelines)Model versioning and registriesData and model monitoring, including drift and performance trackingStrong analytical and communication skills, capable of explaining technical and ML-related trade-offs to both technical and non-technical stakeholdersSecurity & CitizenshipMust be a US CitizenSECRET security clearanceWhat Desired Skills You'll BringAdvanced Education & CertificationsBachelor’s or higher degree in Computer Science, Computer Engineering, or related disciplineRelevant certifications in software architecture, cloud platforms, DevSecOps, or MLOps/ML engineeringSpecialized ExperienceExperience supporting DoD, defense, or C-UAS-related software systemsExperience with distributed, real-time, or high-availability systemsExperience deploying and managing ML models in constrained, real-time, or edge environments (e.g., forward-deployed, on-platform, or tactical systems)Additional Technical SkillsExperience with containerization (Docker), orchestration (Kubernetes), and cloud-native developmentExperience with ML frameworks and ecosystems (e.g., TensorFlow, PyTorch, scikit-learn, ONNX, or similar) and associated deployment stacksFamiliarity with feature stores, experiment tracking tools, and model registries as part of an MLOps workflowFamiliarity with Agile/Scrum methodologies and modern issue tracking/ALM toolsSecurity Clearance RequirementAn active Secret security clearance is required for this position.This position is part of our Federal Solutions team.The Federal Solutions segment delivers resources to our US government customers that ensure the success of missions around the globe. Our intelligent employees drive the state of the art as they provide services and solutions in the areas of defense, security, intelligence, infrastructure, and environmental. We promote a culture of excellence and close-knit teams that take pride in delivering, protecting, and sustaining our nation's most critical assets, from Earth to cyberspace. Throughout the company, our people are anticipating what’s next to deliver the solutions our customers need now.Salary Range: $103,500.00 - $181,100.00We value our employees and want our employees to take care of their overall wellbeing, which is why we offer best-in-class benefits such as medical, dental, vision, paid time off, Employee Stock Ownership Plan (ESOP), 401(k), life insurance, flexible work schedules, and holidays to fit your busy lifestyle!Parsons is an equal opportunity employer, and all qualified applicants will receive consideration for employment without regard to race, color, religion, sex, national origin, disability, veteran status or any other protected status.We truly invest and care about our employee’s wellbeing and provide endless growth opportunities as the sky is the limit, so aim for the stars! Imagine next and join the Parsons quest—APPLY TODAY!Parsons is aware of fraudulent recruitment practices. To learn more about recruitment fraud and how to report it, please refer to https://www.parsons.com/fraudulent-recruitment/.