Enterprise Architecture: Knowledge of enterprise architecture principles, including business architecture, information architecture, and technology architecture.
Proven track record of delivering at least two large-scale enterprise data platform migrations or greenfield builds.
Minimum of 15 years in IT, with at least 4 years in a Solution Architect or Lead Data Engineer role.
Programming: Advanced coding skills in Python, or Java, along with expert-level SQL.
Containerization: Experience with Docker and Kubernetes for deploying data services.
Data Processing: Strong proficiency in batch and stream processing.
Database Systems: Extensive experience managing and querying various systems: Relational: PostgreSQL, MySQL, SQL Server, NoSQL/NewSQL: MongoDB, Cassandra, Warehousing/Lakehouses: Snowflake, Databricks, BigQuery.
Bachelor's or Master's degree in Computer Science, Computer Engineering, Information Systems, or a related field.
Cloud Infrastructure: Expert-level experience with at least one major cloud provider (AWS, Azure, or GCP) and their native data services.

Applied Machine Learning Engineer - ML & AI Systems

TAG - The Aspen Group

Chicago, IL 60290

GenAI Architect

Quotacom

Chicago, IL 60290

Sogeti

Chicago, IL 60290

Yash Technologies

Chicago, IL 60290

Capital One

Chicago, IL 60695

Experience with AI/ML technologies such as Kubernetes, Observability, Security, AI/ML Experiment Management, or Model Monitoring
Currently has, or is in the process of obtaining one of the following with an expectation that the required degree will be obtained on or before the scheduled start date:
A Bachelor's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, Computer Engineering, Software Engineering, Mechanical Engineering, Information Systems or a related quantitative field)
3+ years of experience building business-critical AI and Machine Learning products
Experience in Gen AI Application Evaluation, MLOps, or AIOps
At this time, Capital One will not sponsor a new applicant for employment authorization for this position.
At least 9 years of experience working in Product Management
A Master's Degree in a quantitative field (Statistics, Economics, Operations Research, Analytics, Mathematics, Computer Science, Computer Engineering, Software Engineering, Mechanical Engineering, Information Systems or a related quantitative field) or an MBA with a quantitative concentration