Manager, AI
$149,600–$224,400 year
On-siteSeaTac, Washington, United States
Job Summary
Lead the development and deployment of AI and machine learning models, including GenAI-powered applications, to enhance operational efficiency and revenue optimization across system operations, flight operations, and network planning. Oversee the full AI/ML software development lifecycle, ensuring best practices in model training, evaluation, deployment, and monitoring while establishing scalable frameworks and reusable architectures. Collaborate with Data Engineering, MLOps, and business stakeholders to integrate AI solutions into enterprise systems, guiding the adoption of MLOps practices for versioning, monitoring, and automated retraining. Mentor the team through performance management and stretch assignments to foster an inclusive culture of innovation. Present AI findings to stakeholders, ensuring clear communication of technical concepts, while staying current with advancements in LLMs and transformer-based architectures to assess applicability for business use cases.
Required Qualifications
- 5 years of experience in AI, machine learning, or data science, with a proven track record of deploying AI solutions at scale
- 2 years of leadership experience
- Bachelor's degree in a relevant field, or an additional 2 years of training/experience in lieu of this degree
- Proficiency in Python and experience with AI/ML libraries such as TensorFlow, PyTorch, Scikit-Learn, and XGBoost
- Strong expertise in machine learning, deep learning, and Generative AI (e.g., GPT, BERT, DALL-E, diffusion models, etc.)
- Hands-on experience with cloud platforms (Azure, AWS, or GCP) and AI/ML deployment tools
- Experience with LLM fine-tuning, retrieval-augmented generation (RAG), and prompt engineering
- Experience with MLOps practices, including CI/CD for machine learning, model monitoring, and automated retraining
- Proficiency in Databricks for large-scale data processing and model development
- Strong understanding of data engineering concepts, including data pipelines, ETL, and feature engineering
- Excellent problem-solving skills and ability to translate business challenges into AI solutions
- Effective communication skills, including presenting technical concepts to stakeholders
- Ability to work cross-functionally and influence technical and business teams
- High school diploma or equivalent
- Minimum age of 18
- Must be authorized to work in the U.S.
- post-offer and/or pre-employment drug testing
Desired Qualifications
- Master's or Ph.D. in AI, Data Science, Computer Science, Industrial Engineering, Statistics, or a related field
- Experience in developing enterprise-level GenAI applications, including chatbot development, document summarization, and AI-assisted workflows
- Experience in commercial aviation, logistics, or operational optimization
- Experience integrating AI and GenAI into production systems and enterprise applications
- Knowledge of reinforcement learning, causal inference, or advanced statistical modeling techniques
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