Machine Learning - Senior Software Engineer - Python, DevOps
$232,000–$255,000 year
On-siteAnnapolis Junction, Maryland, United States
Job Summary
Deploy video, image, speech, and text analytics models from research prototypes to production inference services on Kubernetes. Collaborate cross-functionally with end users and researchers to align development with real-world needs, building CI/CD pipelines for Python on NVIDIA Triton Inference Server with TensorRT execution providers. Tune pipelines for throughput and support them through customer transitions while resolving system problems and contributing to hardware/software trade-offs. Create comprehensive user documentation and establish deployment best practices. Requires Top-Secret/SCI clearance, 14 years of SWE experience, and strong Python and DevOps skills. Partial telework available.
Required Qualifications
- A current Top-Secret/SCI with polygraph security clearance
- Fourteen (14) years' experience as a SWE in programs and contracts of similar scope, type, and complexity
- Bachelor's degree in Computer Science or related discipline from an accredited college or university
- Four additional (4) years of SWE experience on projects with similar software processes (substitutable 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
- Must be able to lift 50 lbs
Desired Qualifications
- 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)
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