AI Machine Learning Engineer

Responsibilities

• Research, experiment with, and implement suitable Generative and ML algorithms, tools and technologies.
• Participate in identifying and assessing opportunities i.e. value of new data sources and analytical techniques and technology, to ensure ongoing competitive advantage.
• Accountable for deployment design, development and maintenance of both traditional ML and AI models.
• Collaborate with partners Enterprise Data, Applied AI, Business, Cloud Enablement Team, and Enterprise Architecture teams.
• Delivery of critical milestones for model deployment in the AWS and GCP cloud environments.
• Adept at adopting and promoting MLOps best practices to the Data Science community.

Requirements

• Must be authorized to work in the U.S. now and in the future.
• 1+ years of equivalent experience in a research or DevOps function.
• Development experience developing solutions within AWS, GCP or both.
• Familiarity with building and deploying API services within the Cloud.
• Familiarity building CICD pipelines using Jenkins or equivalent.
• Exposure to with workflow automation platforms (Apache Airflow, Autosys, similar).
• Basic understanding of Data Science model development life cycle.
• Familiarity with emerging data centric technologies such generative AI, Agentic workflows, and embedding LLM’s into automated processes.

Qualifications

• Must be authorized to work in the U.S. now and in the future.

Skills

• Unix
• git
• Strong object oriented development experience using Python

Benefits

• Hybrid work schedule with the expectation of working in an office 3 days a week (Tuesday through Thursday).

Pay

• The listed annualized base pay range is $100,960 - $151,440.

Schedule

• Hybrid work schedule with the expectation of working in an office 3 days a week (Tuesday through Thursday).