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The Senior AWS MLOps Engineer will manage and extend existing ML pipelines in AWS, emphasizing infrastructure as code. Responsibilities include developing documentation, serving as an infrastructure expert, collaborating with data scientists, and identifying optimization opportunities within the cloud infrastructure.

The Lead/Manager of Data Science will oversee multiple projects from inception to conclusion, manage a team of analysts, contribute to business development, and design data science solutions. They will utilize skills in predictive modeling and have robust experience in data cleaning, analysis, and machine learning, specifically in commercial settings.

The VP of Strategic Partnerships will enhance and expand strategic partnerships with industry leaders like AWS and Snowflake, driving growth through relationship development, co-marketing initiatives, and operational excellence. The role involves leading sales enablement, monitoring performance metrics, and representing Blend at industry events.

The VP of Market Expansion leads efforts in engaging and securing Tier 1 customers, focusing on multi-million dollar deals. This role collaborates with sales and growth teams to identify opportunities, craft offerings, and maintain a robust sales pipeline. Key responsibilities include market penetration, deal structuring, leveraging data and AI insights, and ensuring customer success.

As a UI Developer, you will implement user interface designs, optimize front-end performance, ensure device compatibility, and develop reusable component libraries while collaborating with back-end developers and mentoring junior developers.

The Project Manager will lead strategic initiatives to enhance customer experience and optimize Add a Card offers. Key responsibilities include developing action plans, managing multiple cross-functional projects, and collaborating with SMEs. The role demands strong project management skills, adaptability, and excellent communication to engage diverse audiences effectively.

The Manager of AI and Data Engineering will lead a team of data engineers and scientists, build real-time data pipelines, and apply advanced technologies for AI research. Responsibilities include partnering with teams to ensure quality data management and advising leadership on data strategies, while also driving innovation and best practices in AI.