Lucent Innovation - Computer Vision Engineer - Deep Learning/Machine Learning

Description

About The Role

• Develop and implement computer vision algorithms for image classification, object detection, segmentation, tracking, and related tasks.
• Build, train, and optimize deep learning models using frameworks such as TensorFlow, Keras, PyTorch, OpenCV.
• Implement real-time inference pipelines for edge devices, desktop, or cloud environments.
  

Data Pipeline & Preprocessing

• Collect, preprocess, and annotate large image/video datasets.
• Perform data augmentation, normalization, and dataset balancing.
• Work with tools like LabelImg, COCO format, Roboflow, etc.
  

Model Optimization & Deployment

• Optimize models for performance, speed, and accuracy (quantization, pruning, ONNX conversion).
• Deploy models on production environments such as NVIDIA GPUs, TensorRT, ONNX Runtime, Docker,
  

• Develop scalable APIs or microservices to serve CV models.
  

Research & Innovation

• Stay updated with recent advancements in CV architectures (YOLO, DETR, Mask R-CNN, Vision Transformers, etc.
• Experiment with state-of-the-art techniques and propose improvements for model performance.
• Contribute to building reusable modules, libraries, and internal CV & Documentation :
• Work closely with product, engineering, and QA teams to understand project goals and define scalable solutions.
• Document algorithms, model performance metrics, and deployment procedures.
• Participate in code reviews and contribute to team knowledge Skills & Experience Skills :
• 2 - 3 years of experience in Computer Vision, Deep Learning, or ML engineering.
• Strong proficiency in Python and libraries such as NumPy, OpenCV, Pillow.
• Hands-on experience with PyTorch and/or TensorFlow/Keras.
• Experience with CV tasks such as :
• Object detection (YOLO, SSD, Faster R-CNN)
• Segmentation (UNet, Mask R-CNN)
• OCR (Tesseract, EasyOCR, CRNN-based models)
• Feature extraction & image enhancement
• Familiarity with Git, cloud platforms (AWS/GCP), and Linux environments.
  

Soft Skills

• Strong problem-solving and analytical skills.
• Ability to translate business needs into technical solutions.
• Excellent communication and teamwork.
• A continuous learning mindset with passion for AI/ML / Bonus Skills :
• Knowledge of Edge AI : Jetson Nano/Xavier, Coral TPU, Raspberry Pi.
• Experience with MLOps, Docker, CI/CD pipelines.
• Understanding of 3D vision (structure from motion, depth estimation).
• Experience working with time-series video analytics