Ai Ml Engineer

Job Description

Key Responsibilities: Develop and Deploy ML Models: Code and develop software that deploys machine learning models and algorithms into production environments, with a focus on healthcare applications. Communication: Present complex analytics results and concepts to leadership and internal stakeholders in a clear and concise manner. AI/ML Technologies: Employ AI/ML techniques, including NLP, NLU, semantic understanding, intent classification, computer vision, deep learning, and ASR. Deep Learning Applications: Apply deep learning technologies to enable computers to visualize, learn, and respond to complex healthcare situations. Adapt machine learning to areas such as AI, robotics, and other interactive healthcare products. Experimental Methodologies: Apply knowledge of experimental methodologies, statistics, optimization, probability theory, and machine learning for tool building and statistical analysis using both general-purpose software and statistical languages. Job Qualifications: Educational Background: Bachelor's or Master's degree in Computer Science, Engineering, Mathematics, or a related field. Experience: Proven experience in AI/ML engineering, with a strong track record of deploying machine learning models into production, preferably in the healthcare industry. Technical Skills: Proficiency in programming languages such as Python, R, or Java. Experience with machine learning frameworks such as TensorFlow, PyTorch, or similar. Analytical Skills: Strong understanding of experimental methodologies, statistics, optimization, and probability theory. Communication Skills: Excellent verbal and written communication skills, with the ability to present complex information to non-technical stakeholders. Collaboration: Ability to work collaboratively with cross-functional teams, including healthcare professionals, IT, and customer service departments.