Role Overview :

As a Principal AI/ML Architect, you will be at the forefront of designing and implementing cutting-edge AI and Machine Learning solutions. Your day-to-day will involve collaborating with data scientists, engineers, and product managers to translate business requirements into scalable and robust AI architectures. You will guide the team in selecting the right technologies, designing efficient data pipelines, and ensuring the seamless integration of AI models into our products. This role directly impacts our ability to deliver innovative, data-driven solutions to our customers, enhancing user experience and driving significant business growth.

Key Responsibilities :

- Design and implement end-to-end AI/ML architectures, considering scalability, performance, and security, to support various business initiatives.

- Lead the development of data ingestion, processing, and storage solutions, ensuring data quality and accessibility for AI/ML model training and deployment.

- Evaluate and recommend appropriate AI/ML frameworks, tools, and platforms (e.g., TensorFlow, PyTorch, Azure ML, AWS SageMaker) based on project requirements and industry best practices.

- Establish and enforce AI/ML development standards and best practices, including code reviews, testing, and documentation, to ensure high-quality deliverables.

- Collaborate with cross-functional teams to integrate AI/ML models into existing systems and applications, ensuring seamless deployment and monitoring.

- Drive the adoption of CI/CD pipelines for AI/ML model deployment, enabling rapid iteration and continuous improvement.

- Research and evaluate emerging AI/ML technologies and trends, identifying opportunities to enhance our capabilities and stay ahead of the competition.

- Mentor and guide junior team members, fostering a culture of innovation and continuous learning within the AI/ML team.

Required Skillset :

- Demonstrated expertise in designing and implementing scalable AI/ML architectures, leveraging cloud platforms such as Azure or AWS.

- Proven ability to develop and deploy machine learning models using Python and popular frameworks like TensorFlow and PyTorch.

- Strong understanding of data analytics principles and experience with data manipulation and visualization tools.

- Experience with containerization technologies like Docker and orchestration platforms like Kubernetes.

- Proficiency in implementing CI/CD pipelines for AI/ML model deployment and monitoring.

- Excellent communication and interpersonal skills, with the ability to effectively collaborate with cross-functional teams and present technical concepts to both technical and non-technical audiences.

- Bachelor's or Master's degree in Computer Science, Data Science, or a related field.

- Adaptable to a dynamic work environment and comfortable working in a hybrid model.