Associate AI/ML Engineer

Qualifications

• A bachelor’s degree in engineering, computer science, health science, or a related field. • Knowledge in applying AI and machine learning in production environments, showcasing an understanding of healthcare technology. • Knowledge in cloud infrastructure environment and software development tools. • Skill in AI/ML techniques and frameworks. • Skill in collaborating across diverse teams and effectively communicating complex technical concepts to non-technical stakeholders. • Familiarity with best practices in data engineering, data science, AI Engineering, and the MLOps communities. • Strong interpersonal, communication, and time management skills.
• Preferred Qualifications:
• Experience in AI/ML techniques and frameworks, such as deep learning, natural language processing, and Generative AI, with proficiency in tools like Python, TensorFlow, PyTorch, sci-kit-learn, Keras, etc. • Knowledge of the healthcare domain, including clinical workflows, electronic health records, medical terminologies, regulatory requirements, and industry standards. • Familiarity with systems or quality engineering best practices, regulatory standards, and compliance frameworks, with the ability to adapt these effectively to different project scenarios. • Experience in user-centered design, human factors engineering, usability testing methodologies, and evaluation across AI product development. Ability to conduct expert reviews using established usability practices and methods. Presents findings in easy-to-understand terms for the business or clinical practice. • Ability to articulate complex technical concepts to diverse audiences, facilitating clear understanding and engagement from technical and non-technical stakeholders. • Ability to manage a varied workload of projects with multiple priorities and stay current on healthcare trends.

Company