1 month ago
Arlington, VA, USASenior
Responsibilities
- Design and develop machine learning models and applications for deployment to cloud-native services.
- Collaborate with data engineers and data scientists to productionize machine learning models and data pipelines.
- Design and deploy Machine Learning Operations (MLOps) capabilities at scale.
- Integrate AI/ML capabilities into production systems, including model inference APIs, decision-support features, and anomaly detection workflows.
- Design and optimize data models and persistence layers for transactional and analytical workloads.
- Deliver AI and ML features to user-facing applications.
- Create technical design documentation, system diagrams, and architecture artifacts.
- Participate in code reviews, testing, troubleshooting, and reliability improvements.
- Improve system performance, scalability, and reliability as the platform evolves.
- Drive software work from concept through production while collaborating with stakeholders and clients.
Requirements
- 8+ years of professional software development experience.
- Bachelor's degree in Computer Science or a related field is preferred.
- Experience developing microservices in containerized environments.
- Experience with or strong conceptual understanding of LLM-based applications, RAG pipelines, and AI-driven decision systems.
- Experience with Python, relational databases, data warehouses, and integrating AI/ML capabilities into applications.
- Familiarity with MLOps concepts such as model deployment, monitoring, and versioning.
- Ability to produce technical design documentation and design for future scalability and platform evolution.
- Demonstrated ownership, strong problem-solving skills, ability to navigate ambiguity, and excellent communication skills.
- U.S. citizenship and an active Department of War clearance with TS/SCI eligibility are required.
- Experience with Google Cloud Platform or similar cloud environments is preferred.
- Experience designing and consuming RESTful APIs is preferred.
- Experience with API gateways and API management platforms such as Google Apigee is preferred.
- Familiarity with PKI, OAuth2, JWT, LDAP, or SAML authentication and authorization is preferred.
- Experience on U.S. Federal Government programs, particularly Department of War environments, is preferred.
- Google Cloud professional-level certifications are preferred.
Benefits
- Flexible PTO and all Federal holidays off.
- Health, dental, and vision insurance plans.
- Flexible Spending Account, 401k with employer match, and company-sponsored life insurance and disability coverage.
- Professional development through training, certifications, and conferences.
- Paid cloud developer accounts and referral bonuses.
- HQ perks including parking or metro reimbursement, coffee, lunches, and annual social events.
- Access to Washington Capitals and Nationals tickets.
- Located in Patrick SFB, FL, or Arlington, VA; candidates should be local, onsite support may be required, and travel may be up to 25%.
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