AI MACHINE LEARNING ENGINEER

AI MACHINE ENGINEER Must live in Austin, Texas Area Suzy Batiz, the innovative founder of PooPourri and Supernatural, is on the lookout for a bold, abundance-driven, Software Engineer to join our latest venture, The Ninth. This new Brand Incubator and collective agency aims to build captivating brands and products through future-facing technology, Creative problem solving, and years of award winning creative and marketing philosophies. Join the creative powerhouse behind renowned brands like PooPourri and Supernatural at The Ninth, a vibrant new incubator and collective agency spearheaded by Suzy Batiz. We are currently seeking a skilled Software Engineer who specializes in AI Machine Learning. THE JOB: The Ninth is looking for a machine learning engineer to build efficient, data-driven artificial intelligence systems that advance our proprietary automation capabilities. The candidate should be highly skilled in statistics and programming, with the ability to confidently assess, analyze, and organize large amounts of data. Rigorous knowledge of R, Java and Python programming to develop software Designing, developing, and researching Machine Learning systems, models, and schemes In-depth knowledge of machine learning data structures and modeling, software architecture, libraries and frameworks to create AI that accomplishes outlined goals Strong mathematics skills, especially in statistics, to create algorithms Studying, transforming, and converting data science prototypes Training and retraining ML systems and models as needed Advanced analytical skills to interpret test results and performance metrics Creative thinking skills to come up with new solutions and approaches Sound problem-solving skills to refine prototypes and troubleshoot performance issues THE QUALIFICATIONS: A Bachelor or Master' Degree in Computer Science, Artificial Intelligence, Machine Learning, Data Science, or equivalent experience in lieu of degree. 5 years in experience Advanced math and statistics skills in subjects such as linear algebra, calculus and Bayesian statistics. An advanced degree in computer science, math, statistics or related fields. A master's degree in machine learning, neural networks, deep learning or related fields. Strong analytical, problem-solving, communication and teamwork skills. Software engineering skills. Experience in data science. Experience with coding and programming languages, including Python, Java, C++, C, R and JavaScript. Experience working with ML frameworks. Experience working with ML libraries and packages, such as the Natural Language Toolkit. An understanding of data structures, data modeling and software architecture. Knowledge of computer architecture. Knowledge and fluency in cloud platforms such AWS and Google Cloud Services.