Computer Vision Engineer

2 days ago

Hyderabad, Telangana, India Harvested Robotics Full time ₹ 12,00,000 - ₹ 24,00,000 per year

At Harvested Robotics, we build 
AI-powered laser-weeding systems
 for farms in India. We capture high-resolution 
RGB + NIR imagery
, train custom models, and deploy them on rugged edge compute to identify weeds with speed, precision, and safety.

We're looking for a 
Computer Vision Engineer
 who lives at the intersection of algorithms, data, and real-time edge deployment — someone obsessed with accuracy, latency, and pushing models into production on actual machines in the field.

What you'll do

  • Design, train, and optimise CV/ML algorithms for 
    weed detection, crop segmentation, and health classification
    .
  • Build and refine 
    data pipelines
    : labeling, augmentation, dataset versioning, and quality control.
  • Improve 
    accuracy, robustness, and FPS
     across varied farm conditions (lighting, soil, rains, dust).
  • Deploy and optimise models on 
    edge hardware
     (Jetson, Qualcomm, x86, custom accelerators) with tight compute budgets.
  • Implement 
    classical CV + deep learning
     (OpenCV, geometric transforms, segmentation/detection networks).
  • Build and maintain 
    real-time inference pipelines
     using 
    GStreamer, DeepStream
    , CUDA plugins, and custom kernels.
  • Convert and optimise models using 
    TensorRT, ONNX Runtime
    , quantisation (INT8/FP16), and graph optimisation.
  • Work with the perception team on 
    NIR/RGB fusion
    , extrinsic calibration, and sensor synchronisation.
  • Analyse field failures and iterate on models 
    fast
    .
  • Build internal tools for 
    evaluation, visualization, and automated benchmarking
    .

What you need

  • Strong grounding in 
    computer vision, machine learning, and image processing
    .
  • Experience with 
    PyTorch/TensorFlow
    , ONNX, TensorRT, or similar optimisation stacks.
  • Comfort with 
    C++/Python
    , CUDA, and real-time edge deployments.
  • Hands-on experience with 
    GStreamer
     and/or 
    NVIDIA DeepStream
     pipelines.
  • Solid understanding of model evaluation, metric design, class imbalance, and dataset bias.
  • Ability to work with large, messy, real-world datasets.
  • Experience with embedded GPU optimisation, Jetson NX/Orin deployments, or Qualcomm accelerators.
  • Familiarity with robotics perception, ROS, or sensor integration.

Your models directly control 
when, where, and how our robot fires a laser at weeds
. Precision and reliability define product success, safety, and farmer trust. This is not a lab role — your work runs on machines in actual farms every day.

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