Distinguished Machine Learning Engineer- Capital One Software (Remote)

Capital One is a leading financial services company that has embraced technology and data to innovate its services. They are seeking a Distinguished Machine Learning Engineer to join their team, focusing on building and promoting modern technologies while addressing complex business needs that impact customers and associates. The role involves collaboration, mentorship, and driving the adoption of data management tools in the cloud.

Responsibilities:

• Build awareness, increase knowledge and drive adoption of modern technologies, sharing consumer and engineering benefits to gain buy-in
• Collaborate on Capital One’s toughest issues, to deliver on business needs that directly impact the lives of our customers and associates
• Strike the right balance between lending expertise and providing an inclusive environment where others’ ideas can be heard and championed; leverage expertise to grow skills in the broader Capital One team
• Promote a culture of engineering excellence, using opportunities to reuse and innersource solutions where possible
• Effectively communicate with and influence key stakeholders across the enterprise, at all levels of the organization
• Operate as a trusted advisor for a specific technology, platform or capability domain, helping to shape use cases and implementation in an unified manner
• Lead the way in creating next-generation talent for Tech, mentoring internal talent and actively recruiting external talent to bolster Capital One’s Tech talent

Requirements:

• At least 7 years of experience in Software Engineering
• At least 5 years of experience in Machine Learning Systems and Infrastructure
• Masters' Degree
• 7+ years of experience using Python, Java, Go, and SQL
• 6+ year of experience deploying machine learning models
• Ability to understand deploying Machine Learning models in production environments at scale
• Experience using Large Language Models (LLMs) to prompt engineering, fine-tune foundation models and evaluation and alignment of LLMs
• 3+ years of experience with Kafka, Airflow, Spark, AWS Glue/Kinesis
• 3+ years of experience with Databricks or Snowflake
• Experience using LLM Ops tooling and practices in model versioning, deployment, cost optimization and latency reduction
• Bachelors Degree