AI Architect

As an AI Architect at Innovaccer, you will be at the forefront of designing, training, and fine-tuning foundational models 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.

A Day in Life

• Fine-tuning state-of-the-art small language models (SLMs) like Llama-3.1-8B or Phi-3.5-3B on diverse healthcare datasets.
• Evaluating and optimizing various inference and serving frameworks (e.g., Triton, TensorRT, VLLM, TGI).
• Read about the most recent AI model architectures.
• Collaborating with product teams to review and refine architecture designs incorporating AI.
• Troubleshooting AI deployment issues in customer environments, ensuring smooth operation and optimal performance.
• Authoring and presenting technical documentation and white papers and showcasing breakthroughs in internal and external forums.

Responsibilities

• Design, train, and fine-tune advanced foundational models (text, audio, vision) using healthcare-specific datasets, focusing on accuracy and clinical relevance.
• Collaborate with cross-functional teams (product, engineering, clinical) to seamlessly integrate AI/ML technologies into our product offerings.
• Deploy, monitor, and manage AI models in a production environment, ensuring high availability, scalability, and performance.
• Continuously research and evaluate the latest advancements in AI/ML and healthcare industry trends to drive innovation within Innovaccer.
• Create high-quality intellectual property (white papers, case studies, conference presentations) showcasing Innovaccer's technical leadership.
• Ensure all AI solutions adhere to healthcare standards and regulatory requirements (HIPAA, GDPR, etc.).
• Develop and maintain comprehensive documentation for AI models, including development, training, fine-tuning, and deployment procedures.
• Provide technical guidance and mentorship to junior AI engineers and team members.
• Collaborate with stakeholders to understand clinical needs and translate them into technical requirements for model fine-tuning and development.
• Select and curate appropriate datasets for fine-tuning foundational models to address specific healthcare use cases.

Qualifications

• Master's or Ph.D. in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
• Minimum of 7 years of hands-on experience in AI/ML, with a demonstrable track record of training and deploying LLMs and other machine learning models.
• Strong proficiency in Python and familiarity with popular AI/ML frameworks (TensorFlow, PyTorch, Hugging Face Transformers, etc.).
• Practical experience deploying and managing AI models in production environments, including expertise in serving and inference frameworks (Triton, TensorRT, VLLM, TGI, etc.).
• Proven experience in healthcare AI applications, including a solid understanding of healthcare data standards (FHIR, HL7) and regulatory compliance (HIPAA, SOC2, NIST).
• Excellent problem-solving and analytical abilities, capable of tackling complex challenges and evaluating multiple factors.
• Exceptional communication and collaboration skills, enabling effective teamwork in a dynamic environment.
• A strong publication record in top-tier AI/ML conferences (NeurIPS, ICML, KDD, CVPR, AAMAS, etc.) is highly desirable.
• Experience with cloud computing platforms (AWS, GCP, Azure) and containerization technologies (Docker, Kubernetes) is a plus.