Principal AI / ML Engineer

The Principal AI / ML Engineer develops and implements AI / ML models and solutions to drive business innovation and efficiency. This role involves leading AI / ML projects, collaborating with cross-functional teams, and ensuring the quality and impact of AI / ML solutions.

Responsibilities and Duties Lead the development and implementation of AI / ML projects,including the design and development of models and algorithms. Collaborate with stakeholders to understand businessrequirements and translate them into AI / ML solutions. Develop and validate machine learning models, deep learningalgorithms, and statistical analyses. Ensure the accuracy, quality, and relevance of AI / MLoutputs. Stay updated with the latest advancements in AI / MLtechnologies and best practices, applying them to enhance solutions. Mentor and provide guidance to junior AI / ML engineers andother team members. Ensure compliance with data governance, security, andregulatory standards in all AI / ML activities. Prepare and present AI / ML reports and documentation tosenior management and stakeholders. Participate in project planning and contribute to thedevelopment of project timelines and deliverables. Perform other duties relevant to the job as assigned by theHead of Data & AI Engineering or senior management.

Requirements

Bachelor’s degree in AI / ML Engineering, Computer Science, ora related field Relevant certifications (e.g., Google Cloud ProfessionalMachine Learning Engineer, AWS Certified Machine Learning – Specialty) arepreferred Minimum of 8 years of experience in AI / ML engineering orrelated fields Experience in developing and implementing AI / ML solutionsfor AI or technology-focused products Strong programming skills in languages such as Python, R, orJava Proficiency in AI / ML tools and frameworks (e.g., TensorFlow,PyTorch) Excellent problem-solving and analytical skills Strong communication and interpersonal skills Attention to detail and commitment to quality In-depth understanding of AI / ML principles, machine learningalgorithms, and statistical analysis Familiarity with AI / ML model deployment and monitoring Knowledge of data governance, security, and regulatorystandards Ability to manage multiple tasks and prioritize effectively Strong attention to detail and commitment to deliveringhigh-quality work Ability to work independently and as part of a team Programming languages (e.g., Python, R, Java) AI / ML tools and frameworks (e.g., TensorFlow, PyTorch) Data visualization tools (e.g., Tableau, Power BI) Collaboration and communication tools (e.g., Slack,Microsoft Teams) Data management systems (e.g., SQL, NoSQL databases)

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