AI / ML Engineer II

F5•Seattle, WA

1d•Hybrid

About The Position

The AI Center of Excellence is seeking an AI Center of Excellence Engineer to support applied AI research, prototyping, and engineering initiatives. This role helps evaluate emerging AI techniques, develop best practices for applying AI to business and product challenges, and create architecture recommendations for integrating AI capabilities into production systems. The position also supports evaluation of solution effectiveness through defined performance and business outcomes, helping ensure AI efforts deliver practical value. The ideal candidate will bring strong experience in Python, SQL, machine learning experimentation, and modern AI engineering environments, supported by a master’s-level foundation in data science or a related technical field.

Requirements

Master’s degree in Computer Science, Engineering, Data Science, Mathematics, or a related technical field.
2-4 years of relevant industry experience, or equivalent graduate research and internship experience, in machine learning, data science, or applied AI.
Strong programming skills in Python and strong working knowledge of SQL.
Experience developing, evaluating, and analyzing machine learning models in applied or production-oriented environments.
Strong written and verbal communication skills, with the ability to translate technical findings into practical recommendations.
Familiarity with modern AI topics such as transformer architecture, time series analysis, anomaly detection, or generative AI.

Nice To Haves

Exposure to cloud and MLOps environments such as AWS, Azure, GCP, Docker, Kubernetes, CI/CD, MLflow, or Databricks.
Experience with distributed data or ML systems using tools such as Spark or cloud-based processing frameworks.
Understanding of responsible AI, explainability, model monitoring, drift detection, or data quality validation practices.
Hands-on experience using Jupyter for experimentation, analysis, model development, and technical investigation.

Responsibilities

Support research and evaluation of emerging AI, machine learning, and generative AI techniques for product, platform, and business applications.
Build prototypes, proof-of-concepts, and technical experiments to assess feasibility, performance, scalability, and implementation tradeoffs.
Assist in the development of data pipelines, model evaluation workflows, benchmarking processes, and deployment-readiness practices.
Contribute to architecture recommendations and implementation guidance for integrating AI capabilities into products and internal platforms.
Prepare technical documentation, research summaries, and implementation guidance for engineering and cross-functional stakeholders.