AI Architect - NLP / Deep Learning

Responsibilities :

• Work in tandem with our engineering partners to identify and implement the most optimal cloud-based AI solutions for the company
• Research, design and adopt cutting-edge algorithms to address real-world challenges.
• Define and document best practices and strategies regarding deployment and infrastructure maintenance
• Ensure Model performance, uptime, and scale, maintaining high standards of code quality and thoughtful design
• Maintain a platform that automates creating, training, deploying and updating AI models.
• Managing BI Platforms in accordance with company security guidelines
• Build effective relationships with business areas, strategic vendors, and key delivery Requirements Expertise :
• 5+ years of experience in healthcare AI, with a strong understanding of workflows, medical terminologies, and healthcare interoperability standards
• Proven ability to design AI systems that support decision-making, predictive analytics, health management, Proficiency :
• 10+ years in software engineering, data science, or AI, with 5+ years in AI / ML architecture roles.
• Expertise in machine learning, deep learning, natural language processing (NLP), and computer vision applied to healthcare.
• Proficiency in Python, SQL, and ML frameworks such as TensorFlow, PyTorch, and Scikit-learn.
• Experience with cloud platforms (AWS, Azure) and MLOps tools (MLflow, SageMaker).
• Strong understanding of data engineering pipelines, ETL processes, and real-time data & Strategic Experience :
• Demonstrated success in designing scalable, secure, and high-availability AI architectures in healthcare settings.
• Experience with model lifecycle management, including monitoring, retraining, and drift detection in clinical environments.
• Ability to assess and mitigate bias, fairness, and explainability issues in AI models.
• Familiarity with enterprise architecture frameworks and AI governance Behavioral Skills :
• Highly motivated / self-starter with a sense of ownership, willingness to learn, and desire to succeed
• Strong teamwork, problem-solving, and analytical skills
• Strong understanding of Pharma Quality Standards and Practices
• Proven leadership in cross-functional teams, including business teams, data scientists, and IT professionals.
• Strong communication skills to convey complex AI concepts to non-technical stakeholders, including healthcare executives and regulatory bodies.
• Experience in strategic planning, vendor evaluation, and AI capability building within healthcare organizations

(ref : hirist.tech)