Machine Learning Engineer

1. Role: Machine Learning Engineer
   • Experience: 3+ years
   • Notice: Immediate
   • Duration: Minimum 3 Months
   • Budget: To be Determined (TBD)

   • Mandatory Key Skills: Computer Vision | Predictive Analysis/ Time series | Machine Learning | Python |  ML Models |  Numpy | PyTorch | Cloud Platforms| SQL| Excellent Communication

Job Description :

• Proficiency in programming languages such as Python (NumPy, OpenCV, TensorFlow, PyTorch) for developing computer vision algorithms and applications. Knowledge in C++ is a plus. 

• Strong understanding of computer vision fundamentals including image processing techniques (filtering, morphological operations), feature extraction (SIFT, HOG, Optical Flow), object detection (YOLO, SSD, R-CNN), segmentation (U-Net, Mask R-CNN), and tracking. 

• Experience with deep learning frameworks such as TensorFlow, PyTorch, Keras, and OpenCV for developing and deploying deep neural networks for computer vision tasks. 

• Knowledge of popular deep learning architectures for computer vision such as CNNs (Convolutional Neural Networks), RNNs (Recurrent Neural Networks), GANs (Generative Adversarial Networks), and Transformer models. 

• Strong mathematical foundations including linear algebra, calculus, probability theory, and optimization techniques (e.g., gradient descent, Adam optimizer) used in machine learning algorithms. 

• Prior exposure to cloud platforms (preferably AWS) to deploy data pipelines and to use tools/services like AWS SageMaker, Kinesis, MLFlow etc. 

• Exposure to Generative AI algorithms for Computer Vision like Stable Diffusion is a plus. 

• Experience with GPU programming and optimization using CUDA or OpenCL for accelerating deep learning computations is a huge plus.