Staff AI Engineer

The Role

In this role, you will collaborate with cross-functional teams to identify impactful use cases for generative AI, build robust APIs for seamless model integration, and ensure the reliability, scalability, and security of our AI systems. 

This position will report to Engineering Manager - Data and is a remote role.

Responsibilities

• Build and maintain robust APIs that integrate generative AI models into production systems, ensuring scalability and low latency.
• Collaborate with cross-functional teams to identify use cases for generative AI, define requirements, and deliver impactful solutions.
• Implement and optimize workflows for model training, fine-tuning, and inference using large-scale pre-trained models .
• Develop and manage end-to-end pipelines for generative AI models, including preprocessing, model deployment, monitoring, and retraining.
• Conduct experiments to evaluate generative AI models and fine-tune them for real-world performance metrics such as fluency, coherence, and factual accuracy.
• Stay at the forefront of advancements in generative AI research and integrate cutting-edge techniques into the organization’s capabilities.
• Ensure reliability, scalability, and security in the deployment and operation of generative AI systems.
• Document processes, architectures, and technical decisions to facilitate collaboration and future improvements.

Qualifications

• 7+ years of experience ML engineering, with 1 or more years of developing generative AI products.
• You have experience with advanced LLM design patterns, at a minimum with Retrieval-Augmented Generation (RAG).
• You have experience or knowledge of ML traditional techniques (supervised / unsupervised systems or neural networks) and be able to pin point when a solution requires an LLM solution or an ML solution.
• Experience designing and building APIs and deploying them into a production environment.
• You have expertise in MLOps: deployment, model monitoring, and CI/CD workflows.
• You have experience in the GCP ecosystem.
• You have excellent problem-solving, system design, and technology decision-making skills.

Bonus Qualifications

• Familiarity with Snowflake Cortex functionality. 
• Hands-on experience with DBT for transforming and managing data workflows.
• Strong expertise in large language model (LLM) concepts, including prompt engineering, evaluation of AI features and metrics, model fine-tuning, and working with vector databases.