Sr. AI / ML Engineer

The Sr. AI / ML Engineer supports the development and implementation of AI / ML models and solutions to drive business innovation and efficiency. This role involves developing and validating machine learning models, deep learning algorithms, and statistical analyses, collaborating with cross-functional teams, and ensuring the quality and impact of AI / ML solutions.

Responsibilities and Duties Support the development and implementationof AI / ML projects, including the design and development of models andalgorithms. Collaborate with stakeholders to understandbusiness requirements and translate them into AI / ML solutions. Develop and validate machine learningmodels, deep learning algorithms, and statistical analyses. Ensure the accuracy, quality, and relevanceof AI / ML outputs. Stay updated with the latest advancementsin AI / ML technologies and best practices, applying them to enhance solutions. Mentor and provide guidance to junior AI / MLengineers and other team members. Ensure compliance with data governance,security, and regulatory standards in all AI / ML activities. Prepare and present AI / ML reports anddocumentation to senior management and stakeholders. Participate in project planning andcontribute to the development of project timelines and deliverables. Perform other duties relevant to the job asassigned by the Principal AI / ML Engineer or senior management.

Requirements

Bachelor’s degree in AI / ML Engineering,Computer Science, or a related field Relevant certifications (e.g., Google CloudProfessional Machine Learning Engineer, AWS Certified Machine Learning –Specialty) are preferred Minimum of 5 years of experience in AI / MLengineering or related fields Experience in developing and implementingAI / ML solutions for AI or technology-focused products Strong programming skills in languages suchas Python Proficiency in AI / ML tools and frameworks(e.g., TensorFlow, PyTorch) Excellent problem-solving and analyticalskills Strong communication and interpersonalskills Attention to detail and commitment toquality In-depth understanding of AI / ML principles,machine learning algorithms, and statistical analysis Familiarity with AI / ML model deployment andmonitoring Knowledge of data governance, security, andregulatory standards Ability to manage multiple tasks andprioritize effectively Strong attention to detail and commitmentto delivering high-quality work Ability to work independently and as partof a team Programming languages (e.g., Python) 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, NoSQLdatabases)

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