Senior Hybrid Full-Stack ML Engineer-TS/SCI with Poly

Remote, USA • Full-time • Posted 2026-05-31

About the position

We're seeking a Software Engineer to bridge the critical gap between cutting-edge ML research and production-ready solutions. You'll transform research prototypes into robust, deployable systems that end users can confidently put into production. This role uniquely combines software engineering, DevOps practices, and ML solution delivery.

Productionize ML Research : Transform research code and prototypes from our ML team into reliable, scalable solutions ready for end-user deployment
Build Diverse Solutions : Develop applications and services in C++, Java, or Python; create gRPC-based containerized solutions with clients in Java, Python, or GoLang
Own the Delivery Pipeline : Design and maintain CI/CD pipelines, ensuring smooth deployment from development to production
Deploy ML Infrastructure : Configure and optimize containers using NVIDIA Triton Inference Server for high-performance inference
Performance Engineering : Profile, tune, and optimize solutions for production workloads
Documentation & Best Practices : Create comprehensive user documentation and establish deployment best practices
Collaborate Cross-Functionally : Work directly with end users to understand requirements and with researchers to align development with real-world needs

Active TS/SCI with Poly clearance
14+ years of software engineering experience
Strong programming skills in at least two of : C++, Java, Python, or GoLang
Solid understanding of DevOps practices and CI/CD pipelines
Experience with containerization (Docker) and orchestration (Kubernetes)
Experience with machine learning frameworks (PyTorch preferred)
Prior work in ML engineering or ML infrastructure
Ability to write clean, maintainable code with strong software engineering fundamentals
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

ML & AI Technologies Familiarity with ML domains: Natural Language Processing, Computer Vision, Automated Speech Recognition, or Video Processing
Knowledge of model formats and optimization (ONNX, TensorRT)
Technical Stack Protocol Buffers (protobuf) and gRPC NVIDIA technologies (CUDA, TensorRT, Triton Inference Server)
Signal processing techniques and libraries Performance profiling and optimization tools
Professional Experience Experience supporting production ML systems
Background in high-performance computing and/or GPU programming

At CACI, you will receive comprehensive benefits such as; healthcare, wellness, financial, retirement, family support, continuing education, and time off benefits.

Apply tot his job

Apply To this Job

Apply Now