Member of Technical Staff, Real Time Video Streaming

Coram AI
Sunnyvale, US
On-site

Who this role is best for

Aimed at mid-to-senior level engineers with expertise in real-time video processing and edge computing who thrive in collaborative, on-site environments.

Best fit for

  • Candidates with experience in real-time video streaming and edge computing optimization
    — “Building and optimizing real-time video streaming pipelines on our edge devices”
  • Individuals who have deployed ML models in production environments
    — “Deploying machine learning models to production”

Things to consider

  • On-site presence is required for optimal collaboration and speed of execution
    — “Ability to work in an onsite environment - we move quicker when we’re in the same room”
  • Strong familiarity with GStreamer and profiling tools is expected
    — “Strong experience in video processing and streaming (we use GStreamer)”

How to stand out

  • Emphasize experience with real-time data processing and latency optimization in your resume
    — “Experience building applications processing real-time data and optimizing them for latency and memory”
  • Highlight your ability to work on full-stack systems involving edge and cloud components
    — “Coram’s platform cuts across front-end, backend, ML, and high-performance edge computing”
  • Showcase your proficiency in C++ and GPU-based optimizations in your interview responses
    — “Optimizing the platform runtime for maximum performance. This is largely C++ code with parts of the pipeline running on GPU”
  • Demonstrate your experience with observability and telemetry in your interview examples
    — “Building observability and telemetry”
  • Include examples of deploying ML models in production using PyTorch in your application materials
    — “Experience interfacing ML models (we use PyTorch) is a plus”
Pace · Fast PacedCollaboration · HighAutonomy · MediumDecision Impact · Team

Derived from job-description analysis by Serendipath's career intelligence engine.

What success looks like

  • building and optimizing real-time video streaming pipelines
  • deploying machine learning models
  • optimizing platform runtime
Typical background
3+ years of experience writing production software in C++ and Python

Skills & requirements

Required

C++PythonVideo ProcessingReal-time StreamingMachine Learning DeploymentProfiling ToolsDockerCi/cd Pipelines

Preferred

GstreamerGPU OptimizationEdge ComputingInfrastructure ManagementMonitoring Tools

Stack & domain

C++PythonVideo ProcessingStreamingMachine LearningDockerCi/cd PipelinesInfrastructure ManagementMonitoringCommunicationProblem-solvingAIVideo SecurityCloud-native Platform

About the role

Original posting from Coram AI via Ashby

At Coram AI, we’re reimagining video security for the modern world. Our cloud-native platform uses computer vision and AI to help businesses stay safe, make smarter decisions, and move faster; from real-time alerts to seamless clip sharing and multi-site visibility.

You’ll be joining an ambitious, fast-moving team that values clarity, craftsmanship, and impact. Every person here has a voice, ships meaningful work, and helps shape how AI can make the world safer and more connected.

The role:

Coram’s platform cuts across front-end, backend, ML, and high-performance edge computing. You’ll lead major components of our edge-computing stack, with a core focus on real-time video streaming, ensuring Coram Point remains fast, reliable, and intelligent.

Responsibilities:

  • Building and optimizing real-time video streaming pipelines on our edge devices, along with the applications and communication layers that process vision data on compute-constrained hardware
  • Deploying machine learning models to production
  • Optimizing the platform runtime for maximum performance. This is largely C++ code with parts of the pipeline running on GPU
  • Building observability and telemetry

Qualifications:

  • 3+ years of experience writing production software in C++ and Python
  • Strong experience in video processing and streaming (we use GStreamer)
  • Experience building applications processing real-time data and optimizing them for latency and memory
  • Experience using various profiling tools (e.g., gdb, Nsight, Valgrind, flame graph) to optimize the code
  • Experience with Docker, CI / CD pipelines
  • Experience in Edge/IoT computing (we have a fleet of deployed edge computers) is a plus
  • Experience in infrastructure management and monitoring (we use Salt and Grafana) is a plus
  • Experience interfacing ML models (we use PyTorch) is a plus
  • Resilient in challenging and fast-paced environments
  • Exceptional written and verbal communication skills in English, with the ability to influence at all levels
  • Ability to work in an onsite environment - we move quicker when we’re in the same room

What we offer:

  • Flexible paid time off and paid holidays
  • Early-stage equity in a rapidly growing company
  • Referral bonuses
  • Regular team off-sites
  • The latest Apple products and unlimited tech stack (Claude Cowork, Perplexity Computer, Nooks, Clay, Instantly, etc.)

We're on a mission to transform a $50B+ legacy industry by bringing the power of cutting-edge multimodal LLMs and computer vision to real-world security and operations. From firearm detection to intelligent access control, our AI-native platform turns every camera and sensor into a smart system that enhances safety, efficiency, and awareness.

Founded by Ashesh Jain (ex-Lyft Level 5, PhD Cornell) and Peter Ondruska (ex-Lyft, PhD Oxford), Coram AI is backed by Ansa Capital, Battery Ventures, Mosaic, 8VC and Up Partners, have raised over $65M, and were named to the CB Insights AI 100 as one of the most promising AI companies in the world. If you're excited to work on mission-critical AI that makes an impact in the real world, we’d love to meet you.

Source: Coram AI careers (Ashby)

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