Senior IoT Engineer

Viant Technology•Boston, MA

4d•$140,000 - $160,000

About The Position

Viant’s TVision team is redefining television and video audience measurement through a unique combination of computer vision, content recognition, identity-safe measurement, and advanced analytics. Our proprietary technology measures real-world viewer engagement and attention across millions of hours of video content, helping advertisers, publishers, and media owners better understand audience behavior. As a Senior IoT Engineer on the TVision Meter Platform team, you will help define the next generation of TVision’s audience measurement devices. Working at the intersection of embedded hardware, edge AI, computer vision, and Linux systems, you will evaluate emerging hardware platforms, deploy and optimize computer vision models, and build the software that powers our privacy-first measurement technology. This role is ideal for an engineer who enjoys rapidly prototyping solutions, working close to the hardware, and solving complex performance challenges across CPU, GPU, memory, and AI accelerator architectures.

Requirements

Bachelor’s degree in Computer Science, Mathematics, Electrical Engineering, or a related technical field.
5+ years of experience developing embedded, IoT, edge computing, or embedded AI systems.
Experience deploying computer vision or deep learning models on edge devices.
Strong understanding of microprocessors (CPU, GPU, etc.), memory, storage, and system architecture tradeoffs.
Strong Python development skills and the ability to rapidly prototype and validate technical concepts.
Experience developing embedded applications and systems software in C/C++.
Familiarity with Linux kernel interfaces, system services, device drivers, and low-level system troubleshooting.
Experience developing on TensorFlow or Pytorch
Experience with AI inference optimization technologies such as TensorRT, OpenVINO, ONNX Runtime, TensorFlow Lite, or similar frameworks.

Responsibilities

Evaluate CPUs, GPUs, NPUs, and embedded computing platforms to identify the optimal architecture for future TVision measurement devices.
Benchmark computer vision and deep learning workloads across multiple hardware platforms to drive hardware selection and cost optimization decisions.
Prototype and validate edge AI solutions using platforms such as NVIDIA Jetson, Intel Atom, Coral TPU, Rockchip NPU, Qualcomm, and emerging accelerator technologies.
Deploy, optimize, and support multiple computer vision and machine learning models running concurrently on embedded devices.
Analyze system performance including compute utilization, memory consumption, thermal characteristics, power efficiency, and inference latency.
Develop software and systems-level applications in Python and C/C++ to support measurement, device management, and computer vision models.
Work closely with Linux operating system components, including system services, kernel interfaces, device drivers, and hardware integration layers.
Collaborate with Computer Vision, Data Science, and Platform Engineering teams to translate research models into scalable edge deployments.
Rapidly prototype, test, and iterate on hardware and software solutions to improve device capabilities while reducing platform costs.
Influence the long-term hardware roadmap through hands-on evaluation, proof-of-concept development, and technical recommendations