Job Description Velocity Tech has partnered with a rapidly growing tech company that is revolutionizing the video security industry by developing a cutting-edge AI-powered video system. Their next-generation video artificial intelligence provides unparalleled insights and a significantly enhanced user experience compared to traditional solutions in the video security space.

Check you match the skill requirements for this role, as well as associated experience, then apply with your CV below.The team consists of experienced AI and robotics experts, including the CEO and CTO, the company is built on a foundation of technical leadership and innovation. The engineering team brings together talent from top companies and institutions like Lyft, Google, Zoox, Toyota, Facebook, Microsoft, Stanford, Oxford, and Cornell.The RoleThis position involves working across a broad technology stack, including front-end, back-end, edge computing, and machine learning. The primary responsibility will be managing a significant portion of the edge computing stack powering their video AI system.Key responsibilities include:Developing edge applications that process vision data and handle communication layers for compute-constrained edge devices.Deploying machine learning models into production environments.Optimizing runtime performance, primarily in C++, with parts of the pipeline running on GPUs.Building observability and telemetry systems.This role is based in-office 4 days a week.Requirements3+ years of experience in writing production-level software in

C++

and

Python .Experience in building real-time data processing applications, optimizing for

latency

and

memory .Proficiency in using profiling tools like

gdb ,

Nsight ,

Valgrind , and

flame graphs

to optimize code.Familiarity with

Docker

and

CI/CD pipelines .Preferred ExperienceEdge/IoT computing with a deployed fleet of edge devices.Infrastructure management using

Salt .Monitoring systems using

Grafana .Experience with video processing and streaming technologies like

GStreamer .Interfacing with machine learning models using

PyTorch .

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