Senior Software Developer (MLOps)

About the role

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.

About the role

Parsons 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 Doing

Advanced Software Design & Development

• Create logical and functional software code in a variety of programming languages to support Drone Armor capabilities
• Lead the design and implementation of software components, services, and interfaces based on system and mission requirements
• Ensure solutions are robust, secure, maintainable, and aligned with program architecture and coding standards
• Design and implement data and model-serving services that integrate machine learning components into operational C-UAS workflows

MLOps, ML Integration & Lifecycle Management

• Collaborate with data scientists and ML engineers to productionize models, including feature pipelines, inference services, and monitoring
• Implement and maintain end-to-end MLOps workflows, including data ingestion, model training, validation, versioning, deployment, and rollback
• Integrate ML pipelines into CI/CD processes to enable automated testing, packaging, and deployment of models and ML-enabled services
• Establish observability for ML systems (data drift, model performance, latency, accuracy) and support continuous model improvement
• Ensure ML systems meet mission-critical requirements for reliability, explainability, security, and compliance in DoD/defense environments

Technology Evaluation & Trade-Offs

• Understand and articulate the benefits and risks associated with different coding languages and frameworks in various functional environments
• Recommend appropriate languages, tools, and design patterns based on performance, security, maintainability, and integration needs
• Evaluate 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 strategies

Troubleshooting, Debugging & Quality

• React to software problems quickly and effectively, correcting code and related configurations as necessary
• Debug 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 failures
• Support and refine unit, integration, system-level, and ML-specific tests (e.g., data validation, model performance checks) to validate functionality and prevent regressions

Leadership & Collaboration

• Serve as a senior technical resource within the development team, mentoring junior and mid-level developers
• Coach team members on best practices for integrating ML components and MLOps into existing software architectures
• Collaborate with systems engineers, test engineers, data scientists, ML engineers, and field personnel to resolve issues and improve system performance
• Contribute to technical reviews, design walkthroughs, and continuous improvement of development and MLOps practices

What Required Skills You'll Bring

Education

• Bachelor's degree in Computer Science, Electronics Engineering, or other engineering or technical discipline is required with 5 years of experience OR
• 8 years of relevant software development experience may be substituted for education

Experience

• Experience creating logical and functional software code in multiple programming languages
• Experience understanding and clearly articulating the benefits and risks of different coding languages in different functional environments
• Experience reacting to software problems and correcting programs as necessary in complex or mission-critical systems
• Experience deploying, operating, or supporting machine learning models in production environments (MLOps), including monitoring and maintaining ML-enabled services

Technical Competencies

• Proficiency in one or more modern programming languages (e.g., Python, C++, Java, C#, Go, or similar), with working knowledge of others
• Strong grasp of software engineering best practices, including design patterns, code reviews, version control, and CI/CD workflows
• Demonstrated ability to troubleshoot and resolve complex software defects efficiently
• Experience 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 registries
• Data and model monitoring, including drift and performance tracking
• Strong analytical and communication skills, capable of explaining technical and ML-related trade-offs to both technical and non-technical stakeholders

Security & Citizenship

• Must be a US Citizen
• SECRET security clearance

What Desired Skills You'll Bring

Advanced Education & Certifications

• Bachelor's or higher degree in Computer Science, Computer Engineering, or related discipline
• Relevant certifications in software architecture, cloud platforms, DevSecOps, or MLOps/ML engineering

Specialized Experience

• Experience supporting DoD, defense, or C-UAS-related software systems
• Experience with distributed, real-time, or high-availability systems
• Experience deploying and managing ML models in constrained, real-time, or edge environments (e.g., forward-deployed, on-platform, or tactical systems)

Additional Technical Skills

• Experience with containerization (Docker), orchestration (Kubernetes), and cloud-native development
• Experience with ML frameworks and ecosystems (e.g., TensorFlow, PyTorch, scikit-learn, ONNX, or similar) and associated deployment stacks
• Familiarity with feature stores, experiment tracking tools, and model registries as part of an MLOps workflow
• Familiarity with Agile/Scrum methodologies and modern issue tracking/ALM tools

Security Clearance Requirement

• An 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 - $181,100.00

We 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!

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!

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