AI/ML Engineer II
Hybrid · Phoenix, Arizona, United States
Job Summary
Contribute to the development, testing, implementation, and integration of processes with business applications that utilize machine learning model predictions and classifications to inform or drive business activities. Collaborate with Data Scientists to refactor code into IT-maintainable solutions that follow best practices, support GenAI applications, and integrate ML models across data pipelines, APIs, and production systems. Participate in the ML lifecycle from analysis and solution design to data pipeline engineering, testing, deployment, monitoring, and production support. Configure and manage AI/ML infrastructure in cloud/on-prem environments (AWS, GCP, Azure) and tools such as Snowflake, BigQuery, Airflow, Docker, and FastAPI/Flask. Demonstrates proficiency with ML engineering standards, testing scripts, and continuous improvement through learning and documentation.
Required Qualifications
- Bachelor’s degree in Computer Science, Computer Software, Computer Engineering, Information Technology, Applied Sciences, Mathematics, Physics, or related field
- 2 years of work experience in ML engineering or related occupation
- Programming Languages: Pandas, NumPy, PySpark, Snowflake SQL, BigQuery, HTML and CSS
- Machine Learning & NLP Frameworks: Scikit-learn, XGBoost, TensorFlow, PyTorch, NLTK
- Cloud Platforms & Data Infrastructure: AWS, GCP Vertex AI, BigQuery, Cloud Storage; Microsoft Azure; Snowflake Snowpark; OpenShift
- Workflow Orchestration & DevOps: Apache Airflow, GitLab CI/CD, Docker, FastAPI, Flask
- Experience with building ML models, data pipelines, testing, deployment, and production support
- Familiarity with ML development standards and best practices
- Ability to work with cross-functional teams and participate in ML lifecycle tasks
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