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!
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!
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