Software Engineer 2 (Machine Learning) (TS/SCI with Poly)

ML Deployment Engineer moves video,image,speech,and text analytics (VISTA)models from research prototype to production inference services that downstream engineering teams can run in Kubernetes or similar environments. You will work individually or as part of a small research/SDK team to:

• Collaborate cross-functionally working directly with end users to understand requirements and with researchers to align development with real-world neds.
• Build the CI/CD and packaging around Python on NVIDIA Triton Inference Server, with TensorRT execution providers and Business Logic Scripting (BLS) in-service pipelines.
• Tune pipelines for throughput, and support them through customer transition.
• Review and test software components against design requirements.
• Create comprehensive user documentation and establish deployment best practices.
• Resolve system problem reports and contributes to system design, including hardware/software trade-offs, software reuse, infrastructure-as-code, and requirements analysis from the system level down to individual components.

• Top Secret Clearance with Full Scope poly
• Bachelor’s Degree in Computer Science or a related discipline. 14+ years of software engineering experience. Four (4) years of additional software development experience on comparable projects may be substituted for a bachelor’s degree.
• Strong Python experience
• Solid understanding of DevOps practices and CI/CD pipelines
• Intermediate/Advanced experience with containerization (Docker) container creation and performance optimization
• Beginner/Intermediate experience with orchestration tools such as Kubernetes
• Experience taking projects from prototype to production
• Strong communication skills for technical and non-technical audiences
• Self-motivated with ability to work independently and collaboratively

Preferred Qualifications/Experience

• Software Development experience: C++, Java, GoLang, CUDA
• Experience supporting production ML systems
• Familiarity with ML domains: Natural Language Processing, Computer Vision, Automated Speech Recognition, or Video Processing
• Knowledge of model formats and optimization (ONNX, TensorRT)

1. Medical, dental and vision coverage

2. Health Savings Accounts and Flexible Spending Accounts for healthcare and dependent care

3. Flexible work schedule to include onsite, hybrid or remote, as dictated by position

4. 401(k) and company-funded life insurance

5. Generous Paid Time Off (PTO)

6. Tuition and training assistance

7. Financial rewards for employee referrals.

8. Pet insurance

9. Employee discount program