Senior Engineer – AI Delivery

Job Summary

This role supports the deployment and integration of AI models from research into production, ensuring their reliability, scalability, and operational efficiency. It involves collaboration with multiple teams to deliver secure and compliant AI solutions.

Responsibilities

• Deploy ML and LLM models into production using containers or cloud services according to technical requirements.
• Configure deployment parameters, autoscaling, and runtime settings to maintain stable and scalable AI services.
• Monitor production deployments and resolve operational issues affecting model availability and performance.
• Optimize AI model performance, latency, error rates, resource use, and infrastructure costs using techniques like caching, pruning, and quantization.
• Develop AI solutions based on models from GenAI and research teams, including building service layers and APIs.
• Integrate AI solutions with data sources, identity services, logging, and enterprise systems following Elm standards.
• Manage model lifecycle through registries, versioning, controlled releases, and rollback mechanisms, supported by unit and integration tests and CI/CD pipelines.
• Conduct automated and human-in-the-loop evaluations of AI models, monitor data and concept drift, and prepare reports on risks and performance gaps.

Requirements

• Bachelor’s degree in Computer Science, Software Engineering, Artificial Intelligence, Data Science, Computer Engineering, or related field.
• 2–4 years of experience in AI/ML engineering, MLOps, software engineering, AI solution deployment, or related areas.
• Professional certifications in Cloud Computing, MLOps, DevOps, Artificial Intelligence, or Machine Learning are advantageous.

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