Talentgigs
Website:
talentgigs.in
Job details:
We are looking for a Systems-First Computer Vision Engineer who specializes in the "Last Mile" of
AI: taking a model and making it run continuously, reliably, and instantly on live video feeds. This
role is not about training models in a notebook; it is about building the high-performance highways(Pipelines) that allow Vision AI to run in the real world. You will architect robust streaming
architectures using GStreamer/RTSP and optimize inference for ultra-low latency on Edge and Cloud environments.
Key Responsibilities
• Architect Streaming Pipelines: Design and implement robust, real-time video ingestion
pipelines handling multiple RTSP streams using tools like GStreamer, FFmpeg, and
WebRTC.
• Inference Integration: Take trained models from the ML team and integrate them into
production pipelines. Your goal is to ensure the model runs stable, fast, and without memory
leaks.
• Latency Optimization: Obsess over milliseconds. Optimize data processing pipelines to
ensure low-latency inference on both Edge devices (NVIDIA Jetson) and Cloud servers.
• Fault Tolerance: Build "Crash-Proof" systems. Ensure that if a camera goes offline or a frame
is dropped, the system recovers gracefully without manual intervention.
• Framework Evolution: Maintain and evolve our proprietary vision framework by writing
modular, reusable, and efficient Python code/libraries.
• Performance Engineering: Diagnose bottlenecks in the system—whether it's CPU, GPU, or
Network—and implement architectural fixes.
Skills & Requirements
• Video Engineering Mastery: Deep expertise in video streaming protocols (RTSP, WebRTC,
FastRTC) and processing tools (FFmpeg, GStreamer). You know how to handle frame
buffers, decoding, and encoding efficiently.
• Core Vision Stack: extensive experience with OpenCV and Image Processing fundamentals.
You understand geometry, color spaces, and pixel-level manipulation.
• Extensive experience with Redis & RDBMS
KoiReader Technologies, Inc. All Rights Reserved.
• Production Python: Strong experience writing fault-tolerant, multi-threaded/async code.
You understand how to manage resources in long-running processes.
• Deployment Native: Hands-on experience with Docker is mandatory. You know how to
containerize a complex vision application with all its dependencies.
• Mathematical Foundation: Command over geometry and statistics for designing complex
logic layers on top of model detections.
Brownie Points
• Hardware Acceleration: Experience with NVIDIA TensorRT, DeepStream, or Triton
Inference Server for maximizing GPU throughput.
• Framework Knowledge: Familiarity with PyTorch/TensorFlow runtimes (strictly for
inference and loading models).
• DevOps Awareness: Understanding of Kubernetes orchestration and CI/CD pipelines.
• Data Handling: Experience with SQL/NoSQL databases for storing metadata and analytics
results.
What We Offer
• Meritocracy: A candid startup culture where the best ideas win.
• The Playground: Access to the latest NVIDIA Hardware and cutting-edge Generative AI
tools.
• Ownership: Lead a performance-oriented team driven by autonomy and open to
experiments.
• Impact: Design systems for high accuracy and scalability that physically move the global
supply chain.
Click on Apply to know more.