ML Engineer

As a Machine Learning Engineer, you will have the opportunity to contribute your expertise to the development of cutting-edge machine learning capabilities. Your role will involve the following key responsibilities: - 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 various types of large datasets to build robust models. - Architecting large scale data analytics and modeling systems, programming machine learning methods, and integrating them into the ML framework. - Collaborating with data scientists and analysts to support the development of ML data pipelines, platforms, and infrastructure. - Evaluating analyses using statistical methods, ensuring accuracy, and presenting findings effectively. - Creating microservices and APIs for serving ML models, exploring new ML methods, and performing feature engineering to optimize model performance. To excel in this role, you should possess a strong background and knowledge in machine learning, deep learning, natural language processing, and image/signal/video processing. Proficiency in programming languages like Python, Pytorch, MATLAB, C/C++, and Java is crucial. Familiarity with machine learning libraries such as Tensorflow, Keras, scikit-learn, and pyTorch is also essential. Additionally, a solid mathematical foundation with expertise in accuracy, significance tests, visualization, and advanced probability concepts is required. Preferred qualifications for this position include a B.E./B.Tech/B.S. degree with a minimum of 3 years of experience in relevant fields, or an M.E./M.S./M.Tech/PhD in Computer Science with experience in machine learning, image and signal processing, or statistics. As a Machine Learning Engineer, you will have the opportunity to contribute your expertise to the development of cutting-edge machine learning capabilities. Your role will involve the following key responsibilities: - 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 various types of large datasets to build robust models. - Architecting large scale data analytics and modeling systems, programming machine learning methods, and integrating them into the ML framework. - Collaborating with data scientists and analysts to support the development of ML data pipelines, platforms, and infrastructure. - Evaluating analyses using statistical methods, ensuring accuracy, and presenting findings effectively. - Creating microservices and APIs for serving ML models, exploring new ML methods, and performing feature engineering to optimize model performance. To excel in this role, you should possess a strong background and knowledge in machine learning, deep learning, natural language processing, and image/signal/video processing. Proficiency in programming languages like Python, Pytorch, MATLAB, C/C++, and Java is crucial. Familiarity with machine learning libraries such as Tensorflow, Keras, scikit-learn, and pyTorch is also essential. Additionally, a solid mathematical foundation with expertise in accuracy, significance tests, visualization, and advanced probability concepts is required. Preferred qualifications for this position include a B.E./B.Tech/B.S. degree with a minimum of 3 years of experience in relevant fields, or an M.E./M.S./M.Tech/PhD in Computer Science with experience in machine learning, image and signal processing, or statistics.