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 partners.

Basic Requirements :

Domain-Specific Expertise :

- Proven ability to design AI systems that support decision-making, predictive analytics, health management, etc

Technical Proficiency :

- 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 streaming

Architectural & Strategic Experience :

- 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 models.

Preferred Behavioral Skills :

- 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