Principal AI/ML Engineer
Summary
Leads AI/ML projects, designs models, and mentors engineers to build and deploy AI solutions for business innovation.
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)