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Codezyng

AI Developer

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Codezyng

Udupi Full-Time 4–8 yrs exp Posted 1 day ago  · Apply by Sep 14, 2026
Job Title: AI Developer

Experience:2-5 Years

Location: Udupi

Job Summary

We are seeking a passionate and skilled AI Engineer with 2 to 5 years of hands-on experience to join our team. You will be responsible for designing, developing, and deploying machine learning and AI-based solutions that drive value across our products and services. If you have a strong foundation in AI/ML techniques and a desire to build impactful systems at scale, we'd love to connect.

Key Responsibilities

  • Research, design, and implement ML/DL models for video analysis (object detection, classification, tracking, action recognition).
  • Work with large-scale video datasets: preprocessing, annotation, and model training.
  • Optimize deep learning models for accuracy, performance, and scalability in production environments.
  • Collaborate with engineering teams to deploy models into real-time and batch video processing pipelines.
  • Stay updated with the latest advancements in computer vision and ML to integrate into product development.

Requirements

Required Skills & Qualifications:

  • Bachelor's/Master's in Computer Science, AI/ML, Data Science, or related field.
  • 2–5 years of experience in AI/ML with focus on computer vision or video analytics.
  • Strong hands-on experience with Deep Learning frameworks (TensorFlow, PyTorch, Keras).
  • Experience with video analysis techniques: CNNs, RNNs, 3D-CNNs, Transformers for vision, etc.
  • Solid programming skills in Python and familiarity with ML libraries (scikit-learn, OpenCV, NumPy, Pandas).
  • Experience in model deployment, optimization, and inference (TensorRT, ONNX, TorchScript, etc.).
  • Strong problem-solving skills and ability to work in a fast-paced startup-like environment.

Soft Skills

  • Knowledge of video streaming technologies (FFmpeg, GStreamer).
  • Experience with distributed training, GPU acceleration, or cloud-based ML platforms (AWS, GCP, Azure).
  • Familiarity with MLOps tools (MLflow, Kubeflow, Docker, Kubernetes).
  • Publications, Kaggle participation, or open-source contributions in computer vision/ML