Senior Machine Learning Engineer

• Design and implement advanced machine learning algorithms on structured and unstructured data.
• Track and monitor model performance, recommending ongoing improvements to methods and algorithms. 
• Delve deeply into data, understanding its nuances, and implementing best practices in data preprocessing and feature engineering.
• Develop robust, scalable, and efficient data processing and modeling pipelines.
• Evaluate and modify Python libraries to suit project-specific needs.
• Collaborate with cross-functional teams to integrate machine learning solutions into broader product features.

• Master's or Ph.D. degree in Computer Science, Machine Learning, Artificial Intelligence, or related fields.
• Minimum of 5 years of relevant experience in machine learning or AI-focused roles.
• Proven experience in traditional machine learning techniques and methodologies, including proficiency in developing, evaluating, and deploying AI/ML algorithms.
• Experience with large language models and natural language processing is highly preferred, including experience with both open-source and closed-source generative AI models.
• Strong programming skills in Python, with preferred experience in deep learning and big data libraries.
• Experience with cloud-native tools, services, and computing environments.
• Demonstrated ability to work on complex, end-to-end projects within a team setting.
• Ability to approach complex problems methodically and creatively, coming up with innovative solutions.
• Strong desire to continuously learn and apply new technologies and frameworks. 
• Preferred experience or familiarity with the healthcare industry.
• Must be authorized to work in the United States and available to work in Austin, TX.

Last updated on Oct 25, 2024