Software Engineer
2 weeks ago
Technology Stack:
Enterprise and Saas Experience Worked on ML/AI cloud native ML products, Data Science tools, and ecosystem Hands-on experience building and running highly technical and scalable teams Work with product/customer teams on how machine learning can make their product or system better
Management/Leadership Stack:
Experience building and leading expert machine learning teams that have routinely launched new products and features that drive significant revenue and engagement with machine learning. Experience developing machine learning products and capabilities in a cloud environment with a good understanding of the product and sales side of the business Experience with prioritizing and adding new machine learning-based features and capabilities, launching new products to drive revenue Capacity plan pre-sales and post-sales support from within the team. Drive horizontal engineering efforts that improve the efficiency of the pre-sales and post-sales organizations. Work with multiple stakeholders within Product, Sales, and Engineering and with Customers to plan releases.
Customer Advocacy Stack:
Candidate should have the business, strategic, and technical background to understand the customer needs to innovate new features and product ideas Visionary thinker: Should be able to develop plans for customer acquisition and growth plan, strategic partnership and should be able to interact with internal and external leadership to be successful. Great presentation skills - for our typical audience - technical and executive staff for product demos as well as whiteboard machine learning solutions to business problems Preferred / Good to have Qualifications
- Big and small company experience
- Open source Saas product experience
- GNN/Graph Experience
- Closely worked with product and sales and should be able to update product/feature/customer updates to the executive staff
We are an equal opportunity employer and value diversity at our company. We do not discriminate on the basis of race, religion, color, national origin, gender, sexual orientation, age, marital status, veteran status, or disability status.
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