Location: Remote | Employment Type: Full Time
About the Role
As 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 role
What We’re Looking For
Required
- 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 environments
Preferred
- 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.
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