Hiring: Edge AI/Model Optimization Engineer Company: NextGen Federal Systems Location: Aberdeen, MD Job Posted Time: 2026-09-10 10:30:45 Target Skills & Keywords : AI, CI/CD, Docker, Embedded Systems, Kubernetes, LLM, Linux, ONNX, Ollama, Python, TensorRT, vLLM About the job Experience: •5+ years of experience supporting AI/ML deployment, model optimization, edge computing, GPU acceleration, or AI inference operations Required Skills: •Evaluate candidate Large Language Models (LLMs), embedding models, and AI inference solutions for quality, latency, memory utilization, reliability, and operational performance on embedded GPU-enabled edge compute platforms, including the X9 Spider Mission Computer architecture •Tune and optimize AI model runtime configurations for edge deployment, including quantization strategies, batching configurations, context window sizing, cache behavior, inference scheduling, and GPU memory utilization specific to operational edge hardware environments •Partner cross-functionally with customer stakeholders to assess mission requirements and evaluate alternative edge compute platforms when operational demands exceed X9 Spider capabilities or when cost, performance, power, size, weight, or thermal tradeoffs require additional analysis •Benchmark agentic AI workflows, inference pipelines, and model-serving architectures against target hardware constraints and operational performance thresholds •Recommend model-selection, runtime, and configuration tradeoffs balancing mission effectiveness, latency, throughput, resource utilization, reliability, and operational sustainability •Build and maintain repeatable performance and stress-testing frameworks for evaluating latency, throughput, tool-call overhead, failover behavior, degraded-resource conditions, and disconnected operational scenarios on edge compute platforms •Package, deploy, validate, and sustain local model-serving components and inference services to support reliable operation within tactical and edge environments •Partner cross-functionally with agent engineers, AI developers, and integration teams to validate that agent behavior, workflow reliability, and operational outcomes remain acceptable following model compression, quantization, runtime optimization, or hardware configuration changes Qualifications: •Bachelor’s degree in Computer Science, Electrical Engineering, Computer Engineering, Data Science, Artificial Intelligence, or related technical discipline •Operational familiarity with Python and AI/ML deployment frameworks commonly used for edge inference and operational AI systems •Strong analytical, troubleshooting, and performance optimization skills •Demonstrated capacity to communicate technical findings and operational tradeoffs effectively to technical and non-technical stakeholders •Active Security Clearance is required •Operational familiarity with X9 Spider Mission Computer architectures or similar embedded GPU-enabled mission systems Interested candidates, please apply directly through the job posting on company's career page or try via AI auto apply on this platform. Don't miss this opportunity to join a forward-thinking team!