AI Research Scientist - Machine Learning

Our client is at the forefront of innovation and is seeking a brilliant AI Research Scientist specializing in Machine Learning to join their cutting-edge team in Denver, Colorado, US . This role offers a hybrid work model, blending the benefits of remote flexibility with collaborative in-office sessions. You will be instrumental in developing and implementing novel AI algorithms and machine learning models to solve complex real-world problems across various domains. Your work will involve deep research, experimentation, and pushing the boundaries of artificial intelligence.

Key responsibilities include designing, building, and evaluating machine learning models for tasks such as natural language processing, computer vision, predictive analytics, and reinforcement learning. You will conduct rigorous scientific research, analyze large datasets, and stay abreast of the latest advancements in AI and machine learning. The successful candidate will collaborate closely with engineers, data scientists, and product managers to translate research findings into practical applications. This role demands a strong theoretical foundation in machine learning, statistics, and computer science, along with practical experience in programming languages like Python and associated libraries (e.g., TensorFlow, PyTorch). Exceptional problem-solving skills, creativity, and a passion for discovery are essential. As part of our hybrid model, you will engage in regular team meetings and brainstorming sessions at our Denver, Colorado, US office, while also having the flexibility to work remotely. We foster an environment of continuous learning and encourage contributions to the broader AI community. This is an exceptional opportunity to shape the future of AI with a forward-thinking organization.

Qualifications

Ph.D. or Master's degree in Computer Science, Artificial Intelligence, Machine Learning, Statistics, or a related quantitative field. 3+ years of hands-on experience in developing and deploying machine learning models. Proficiency in Python and deep learning frameworks (TensorFlow, PyTorch, Keras). Strong understanding of various machine learning algorithms, including deep neural networks, SVMs, and ensemble methods. Experience with data preprocessing, feature engineering, and model evaluation techniques. Excellent research capabilities, publication record is a plus. Strong analytical and problem-solving skills. Effective communication and collaboration skills, with experience in hybrid work environments. Familiarity with cloud platforms (AWS, GCP, Azure) is beneficial.