Your Role
As a Senior AI Engineer/Architect at Innovaccer, you will be at the forefront of designing, training, and fine-tuning foundational large language models (LLMs) with healthcare-specific data. You will be critical in integrating these technologies into our healthcare products, ensuring they operate effectively in a production environment. Your expertise will help us to revolutionize healthcare delivery, improve patient outcomes, and maintain compliance with industry regulations.
Key Responsibilities
● Design, train, and fine-tune state-of-the-art foundational LLMs using healthcare-specific datasets to ensure high accuracy and relevance in clinical applications.
● Collaborate with cross-functional teams to integrate AI/ML technologies into product offerings.
● Deploy, monitor, and manage AI models in a production environment, ensuring high availability and performance.
● Stay abreast of the latest AI/ML advancements and healthcare industry trends to drive innovation within the company.
● Ensure that all AI solutions comply with healthcare standards and regulatory requirements, including HIPAA, GDPR, and other relevant frameworks.
● Develop and maintain documentation for AI models, including model development, training procedures, fine-tuning strategies, and deployment plans.
● Provide technical leadership and mentorship to junior AI engineers and team members.
● Work closely with stakeholders to understand clinical needs and translate them into technical requirements for model fine-tuning.
● Evaluate and select appropriate datasets for fine-tuning LLMs to meet specific healthcare use cases.
What You Need
● Master’s or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
● Minimum of 5 years of experience in AI/ML, with a proven track record of training and deploying LLMs and machine learning models.
● Strong programming skills in Python, and familiarity with AI/ML frameworks such as TensorFlow, PyTorch, or similar.
● Experience with deploying and managing AI models in production environments, including knowledge of MLOps practices.
● Prior experience in healthcare AI applications, with a solid understanding of healthcare data standards (e.g., FHIR, HL7) and regulatory compliance.
● Excellent problem-solving and analytical skills, with the ability to work on complex problems where analysis of situations requires an in-depth evaluation of various factors.
● Strong communication and collaboration skills, with the ability to work effectively in a team-oriented environment.
● Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and containerization technologies (e.g., Docker, Kubernetes) is highly desirable.