3 Endtoend Solutions Jobs

As a Machine Learning Engineer, you will be leveraging your expertise to contribute towards the development of cutting-edge capabilities within the realm of machine learning. Your responsibilities will encompass various facets of the software development lifecycle for ML solutions, including design, deployment, testing, maintenance, and enhancement. Your primary duties will involve the application of machine learning, deep learning, and signal processing techniques on extensive datasets comprising audio, sensors, images, videos, and text for model development. You will also play a crucial role in architecting large-scale data analytics and modeling systems, designing and programming machine learning methods, and integrating them into the ML framework and pipeline. Collaborating closely with data scientists/analysts, you will support the development of ML data pipelines, platforms, and infrastructure, along with evaluating and validating analyses using statistical methods. Creating microservices and APIs for serving ML models and services, evaluating new machine learning methods, and implementing feature engineering to enhance model performance will be integral aspects of your role. You are expected to possess a strong background and knowledge of recent advancements in machine learning, deep learning, natural language processing, and image/signal/video processing, backed by approximately 5 years of professional experience in real-world applications. In addition, proficiency in programming, familiarity with machine learning libraries such as Tensorflow, Keras, scikit-learn, and pyTorch, exceptional mathematical skills, and the ability to architect and implement end-to-end solutions for accelerating experimentation and model building are crucial requirements. An understanding of a variety of machine learning techniques like clustering, decision tree learning, and artificial neural networks, coupled with the capability to conduct independent and collaborative research, is highly valued. Strong written and verbal communication skills are essential for effective collaboration and articulation of ideas. This role offers a dynamic opportunity to contribute to the advancement of ML capabilities and work on challenging projects in a stimulating environment.,

As a Machine Learning Engineer, you will utilize your expertise to contribute to the development of a world-leading capability in the domain of machine learning. Your responsibilities will involve participating in the design, development, deployment, testing, maintenance, and enhancement of machine learning software solutions. You will be tasked with applying machine learning, deep learning, and signal processing techniques to large datasets such as audio, sensors, images, videos, and text in order to develop models. Additionally, you will be responsible for architecting large-scale data analytics and modeling systems, designing and programming machine learning methods, and integrating them into the ML framework and pipeline. Collaboration with data scientists and analysts to support the development of ML data pipelines, platforms, and infrastructure will be a key aspect of your role. You will also evaluate and validate analysis using statistical methods and present findings in a clear manner to individuals not well-versed in the fields of data science and computer science. Furthermore, you will create microservices and APIs for serving ML models and services, evaluate new machine learning methods for adoption, and conduct feature engineering to enhance model performance. Your background should include knowledge of recent advances in machine learning, deep learning, natural language processing, and image/signal/video processing, with at least 5 years of professional experience in real-world applications. Strong programming skills in languages such as Python, Pytorch, MATLAB, C/C++, and Java, along with familiarity with software engineering concepts like OOP and design patterns, are essential. Proficiency in machine learning libraries such as TensorFlow, Keras, scikit-learn, and PyTorch is required. Additionally, you should possess excellent mathematical abilities, including expertise in accuracy, significance tests, visualization, and advanced probability concepts. Experience in architecting and implementing end-to-end solutions for accelerating experimentation and model building is highly desirable. A working knowledge of various machine learning techniques (clustering, decision tree learning, artificial neural networks, etc.) and the ability to conduct independent and collaborative research are crucial for success in this role. Strong written and verbal communication skills are also important. Candidates with a B.E./B.Tech./B.S. degree and at least 3 years of experience in machine learning, deep learning, natural language processing, or image/signal processing will be considered. Preferably, candidates with an M.E./M.S./M.Tech./PhD in fields related to Computer Science and experience in machine learning, image and signal processing, or statistics are preferred for this position.,

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. You will work on applying machine learning, deep learning, and signal processing techniques on large datasets such as audio, sensors, images, videos, and text to develop models. Additionally, you will be involved in architecting large scale data analytics and modeling systems, designing and programming machine learning methods, and integrating them into the ML framework and pipeline. Collaboration with data scientists and analysts to support the development of ML data pipelines, platforms, and infrastructure will be a key aspect of your role. You will evaluate and validate analyses using statistical methods and present findings in a clear manner to individuals not familiar with data science or computer science. Furthermore, you will create microservices and APIs for serving ML models and services, evaluate new machine learning methods, and perform feature engineering to enhance model performance. The required skills for this role include a background and knowledge of recent advances in machine learning, deep learning, natural language processing, and image/signal/video processing, with around 5 years of professional work experience in real-world applications. Proficiency in programming languages such as Python, Pytorch, MATLAB, C/C++, and Java, along with knowledge of software engineering concepts like OOP and design patterns, 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. You should be capable of architecting and implementing end-to-end solutions for accelerating experimentation and model building, as well as possessing knowledge of various machine learning techniques such as clustering, decision tree learning, and artificial neural networks. The ability to conduct both independent and collaborative research, along with excellent written and spoken communication skills, is crucial. 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.,