AIML Engineer, Applied AIML

JOB SUMMARY:

The AI/ML Engineer will collaborate closely with a team of skilled data scientists to develop innovative solutions that enhance guest experiences at our destinations and boost engagement with our digital products. This role requires a solid background in computer science data engineering machine learning and technology. The engineer will be responsible for designing developing and maintaining large-scale AI/ML systems that improve guest experiences increase relevancy and drive operational efficiencies. Key responsibilities include ensuring smooth data integration into AI systems orchestrating model selection and automating AI/ML pipelines. The role also involves overseeing testing monitoring and optimizing ML pipelines in production while adhering to the highest standards in ML Ops and AI Ops.

MAJOR RESPONSIBILITIES:

AI and ML Ops

• Testing & Monitoring in Production: Implement continuous integration and deployment (CI/CD) for models. Test monitor and ensure the smooth operation of models in production environments addressing issues proactively.
• ML Ops & AI Ops: Ensure best practices in ML and AI operations focusing on model versioning reproducibility scalability and performance.
• Collaboration: Work closely with data scientists software engineers and product teams to ensure successful integration of AI models into production systems.
• Performance Tuning & Optimization: Continuously improve the performance of ML models and pipelines ensuring they meet business and technical requirements.
• Documentation & Compliance: Maintain comprehensive documentation for models pipelines and operational procedures. Ensure compliance with data security and privacy policies.

AI/ML Application Development

• Design implement and automate end-to-end ML pipelines from data preprocessing to model deployment and monitoring.
• Build and maintain pipelines that efficiently integrate large datasets into ML/AI models ensuring data is clean relevant and scalable.
• Lead the model selection process balancing between various LLMs and other AI models. Develop robust orchestration systems to deploy models efficiently.
• Integrate models into AI-driven applications and workflows optimizing them for performance and business use cases.

Data Enablement

• Collaborate on building secure ETLs application data integrations data workflows data pipelines APIs and automate data preparation jobs for analysis consumptions BI & reporting delivering data to other application and platforms. Optimize data flow and processing performance secure sharing automated monitoring and alerts.
• Engage with internal/external partners to gather requirements and collaborate with technology engineers architects and data scientists to help in designing a robust data enablement solution.
• Understands and actively participates in Environmental Health & Safety responsibilities by following established UO policy procedures training and team member involvement activities.
• Performs other duties as assigned.

EDUCATION:

• Bachelors degree in Computer Science Engineering Data Science or in a relevant applied quantitative field is required.
• Masters is preferred.

EXPERIENCE:

• 3 years of hands-on experience in data engineering or data science working with cross-functional teams to implement data and ML/AI solutions in real-world applications.

ADDITIONAL INFORMATION:

• Carries out supervisory responsibilities in accordance with the organizations policies and applicable laws.
• Proficiency in Python with expertise in ML frameworks like TensorFlow PyTorch or Keras and experience writing production-level code for model training and deployment.
• Expertise in cloud platforms for model deployment scaling and operationalization with a preference for experience in serverless architecture and cloud storage solutions.
• Familiarity with real-time data integration and streaming platforms integrating streaming data sources into AI/ML workflows to enable real-time learning.
• Proficiency in building and automating ML pipelines with the ability to orchestrate multiple models and data streams automating from ingestion to deployment and monitoring.
• Extensive experience with ML Ops/AI Ops frameworks for model monitoring version control and CI/CD ensuring model accuracy and managing the production lifecycle. Strong experience with CI/CD tools for automating model deployment testing and version control in dynamic environments.
• Knowledge of DevOps practices for AI/ML pipeline automation including infrastructure-as-code containerization and orchestration.
• Proven ability to work in cross-functional teams and translate business needs into AI/ML solutions communicating technical concepts to non-technical stakeholders.
• Strong communication skills to effectively present AI/ML insights and collaborate with internal and external teams.
• Experience defining and tracking success metrics for AI/ML initiatives and aligning them with business objectives.
• Stay current with AI/ML advancements particularly in LLMs and apply new methods to improve model performance.

Your talent skills and experience will be rewarded with a competitive compensation package.

Universal Orlando Resort. Here you can.