AI/ML Engineer, Innovation Lab (AI & Analytics Lab), Business Technology

Develop and maintain AI/ML models and applications:

• Design and implement machine learning models tailored to specific business needs.
• Continuously monitor and update models to ensure they remain accurate and effective.
• Develop applications that integrate AI/ML models, providing end-to-end solutions for various use cases.

Perform data preprocessing, feature engineering, and model training:

• Clean and preprocess raw data to remove noise and inconsistencies, ensuring high-quality input for models.
• Apply feature engineering techniques to create meaningful features that enhance model performance.
• Train models using appropriate algorithms and techniques, optimizing for accuracy and efficiency.

Collaborate with cross-functional teams to gather requirements and deliver solutions:

• Work closely with stakeholders from different departments to understand their needs and objectives.
• Translate business requirements into technical specifications for AI/ML solutions.
• Deliver tailored solutions that address specific challenges and add value to the organization.

Debug and troubleshoot AI/ML models and applications:

• Identify and resolve issues related to model performance, such as overfitting or underfitting.
• Debug application code to ensure smooth integration and functionality of AI/ML models.
• Perform root cause analysis to address any anomalies or errors in the models and applications.

Participate in code reviews and contribute to team success:

• Engage in regular code reviews to ensure code quality and adherence to best practices.
• Provide constructive feedback to peers and incorporate suggestions to improve your own code.
• Collaborate with team members to achieve project milestones and contribute to the overall success of the team.

Ensure compliance with coding standards and best practices:

• Write clean, maintainable, and well-documented code that follows industry standards.
• Stay updated with the latest coding practices and integrate them into your work.
• Conduct peer reviews to maintain high standards of code quality and consistency.

Continuously improve technical skills and knowledge:

• Engage in continuous learning through online courses, workshops, and reading relevant literature.
• Experiment with new tools and technologies to understand their potential applications. Attend conferences, webinars, and meetups to network with professionals and learn from experts.

Job Complexity & Problem Solving

• Continuously develop technical skills to keep up with technology advancements.
• Ability to debug and troubleshoot complex AI/ML models.

Leadership & Stakeholder Management

• Ability to develop and maintain high-quality AI/ML models.
• Strong problem-solving and debugging skills.
• Ability to work collaboratively in a team environment.

Technical Competencies

• Working knowledge for cloud development (Containerization, Cloud Services (AWS, Azure), API Design, Microservice Architecture)
• Ability to deploy AI models into production effectively and at scale.
• Strong understanding in LLM techniques, for ex: tokenization, RAG, Reinforcement Learning and etc.
• Experience with data preprocessing, feature engineering, and model training.
• Capability to stay abreast of new research and integrate the latest advancements.
• Academic Qualifications: At least a Bachelor’s degree in Computer Science, Data Science, or a related field.
• Minimum of 2 years of experience in AI/ML development.
• Proficiency in programming languages such as Python/Java.
• Strong problem-solving and debugging skills.
• Ability to work collaboratively in a team environment.