Machine Learning System Engineer

Location: Hybrid | Employment Type: Full TimeAbout the RoleAs a Machine Learning System Engineer, you will design, build, and deploy advanced machine learning and computer vision systems for real-time applications. You will translate high-level product requirements into scalable system architectures, drive execution across complex software stacks, and deliver high-performance perception and edge AI systems in an Agile environment.What You’ll Accomplish • Develop deep learning and computer vision systems, including CNN- and transformer-based perception pipelines for real-time applications. • Own ONNX → TensorRT export and optimization workflows for edge deployment on Jetson- class hardware. • Profile, benchmark, and optimize all system modules against strict latency and power budgets. • Build and maintain the full edge inference runtime (model loading, orchestration, memory management, power monitoring) • Design and enforce CI/CD pipelines for model validation, regression testing, and performance guardrails (latency + accuracy). • Oversee hardware-in-the-loop testing on NVIDIA Jetson platforms (Orin Nano, Orin NX, etc.). • Guide development of imaging and video processing pipelines using Python, C++, OpenCV, PyTorch, TensorFlow, and MATLAB. • Build camera and video ingestion pipelines on Jetson (DeepStream, GStreamer, VPI, libargus/V4L2) using zero-copy, GPU-resident buffers. • Translate product requirements into scalable, production-ready technical solutions. • Drive system architecture decisions across perception, ML inference, and edge deployment stacks. • Design and implement autonomous perception algorithms for real-time perception and decision-making systems. • Develop and optimize ADAS features supporting vehicle safety and driver assistance capabilities. • Ensure reliable delivery of GPU-accelerated, real-time robotics and vision systems.Role Level & Scope • Individual contributor roleWhat We’re Looking ForRequired • Bachelor’s degree in Computer Science, Software Engineering, Computer Engineering, or equivalent • 5+ years of software development experience • Ability to translate complex technical concepts into clear, accessible language for non- technical stakeholders. • Strong background in machine learning and deep learning (CNNs and transformers) • Experience with computer vision and video processing (detection, classification, 3D/stereo vision, point clouds) • Proficiency in Python, C++, and tools such as PyTorch, OpenCV, and MATLAB • Experience with imaging systems, image processing, and GPU-accelerated computing • Strong systems engineering and architecture experience across complex software stacks • Ability to translate product requirements into technical solutions and drive Agile execution • Experience with configuration management in multi-system environmentsPreferred • Experience leading or managing software engineering teams • Thermal imaging experience or familiarity • Experience optimizing and evaluating neural network performance in production systems • Valid driver’s license or ability to obtain one within the first 6 months of employment. • Background: bringing R&D technologies into production or commercialization • Deep experience with NVIDIA TensorRT, CUDA, and Jetson SDK • Strong profiling expertise using tools like nsys / nvprof to identify bottlenecks • Understanding of FP16/INT8 quantization tradeoffs and calibration workflows, including quantization-aware training (QAT) when post-training quantization underperforms • Experience with edge inference runtimes or serving systems (not just cloud MLOps) • Strong systems programming skills (C++/Python, memory management, multi-process orchestration) • Experience implementing multi-rate scheduling systems (perception, SLAM, tracking at different frequencies) • Familiarity with Jetson Orin Nano hardware constraints (no DLA, no hardware video encoder, unified CPU–GPU memory, zero-copy buffer management, 4–8 GB budget)Compensation Range$100k – $140k annually, based on experience, qualifications, and geographic location, plus applicable benefits.Apply for this roleOpens an email to hr@owlai.us with the role title filled in. Attach your CV and tell us briefly why this one.