ML Engineer

As a Machine Learning Engineer at Cognida.ai, you will play a crucial role in designing and developing machine learning algorithms and deep learning applications. Your responsibilities will involve solving complex problems with multilayered data sets, optimizing existing machine learning libraries, analyzing datasets to uncover insights, and collaborating with various teams to ensure accurate user recommendations. Your primary goal will be to ensure that algorithms generate precise user recommendations and enhance system performance through the implementation and testing of various search and recommendation algorithms. Key Responsibilities: - Design and develop machine learning algorithms and deep learning applications and systems. - Solve complex problems with multilayered data sets and optimize existing machine learning libraries and frameworks. - Analyze complex datasets to uncover insights and patterns that aid in model development. - Collaborate with data scientists, administrators, data analysts, data engineers, and data architects on production systems and applications. - Identify discrepancies in data distribution that could impact model performance in real-world applications. - Ensure algorithms produce accurate user recommendations. - Implement and test various search and recommendation algorithms to enhance system performance. - Optimize existing machine learning models for performance and scalability. - Study and transform data science prototypes and apply appropriate machine learning algorithms and tools. - Extend existing machine learning libraries and frameworks. Qualifications: - ML Engineer with 5+ years of experience. - Previous experience in Generative AI, including building annotations and models. - Strong math and computer skills, with a deep understanding of probability, statistics, and algorithms. - Proficiency in machine learning frameworks such as Keras or PyTorch. - Familiarity with data structures, data modeling, and software architecture. - Knowledge of Python, Java, and R programming languages. - Excellent communication and collaboration skills. - Ability to work effectively with cross-functional teams and client managers.,