ML Engineer

As a Machine Learning Engineer, you will be applying your expertise to help develop a world-leading capability in the domain of machine learning. Your responsibilities will include: - Contributing to the design, development, deployment, testing, maintenance, and enhancement of machine learning software solutions. - Applying machine learning, deep learning, and signal processing techniques on large datasets such as audio, sensors, images, videos, and text to develop models. - Architecting large scale data analytics and modeling systems, designing and programming machine learning methods, and integrating them into the ML framework and pipeline. - Collaborating with data scientists and analysts to support the development of ML data pipelines, platforms, and infrastructure. - Evaluating and validating analyses using statistical methods and presenting findings in a clear manner. - Creating microservices and APIs for serving ML models and services, evaluating new machine learning methods, and performing feature engineering to enhance model performance. You should have a background and knowledge of recent advances in machine learning, deep learning, natural language processing, and image/signal/video processing. Proficiency in programming languages such as Python, Pytorch, MATLAB, C/C++, and Java is essential. Familiarity with machine learning libraries such as Tensorflow, Keras, scikit-learn, and pyTorch is also required. A strong mathematical background with skills in accuracy, significance tests, visualization, and advanced probability concepts is necessary. Preferred qualifications include a B.E./B.Tech/B.S. degree with 3+ years of experience in the relevant fields or an M.E./M.S./M.Tech/PhD, preferably in Computer Science, with experience in machine learning, image and signal processing, or statistics.,