Machine Learning Lead – Azure Infrastructure Workload
- Location-United States
- Company-Microsoft Azure
- Job type-Remote,Full-time
- Experience level-Mid -senior level
Required Qualifications
- 7+ years technology-related sales or account management experience
- OR Bachelor’s Degree in Computer Science, Information Technology, Business Administration, or related field AND 6+ years technology-related sales or account management experience.
- 3+ years of Machine Learning technical or technical sales experience in enterprise public cloud-based solutions.
Preferred Qualifications
- Project management experience.
- Experience delivering status updates to executive-level stakeholders.
- Experience with the AI partner ecosystem and the ability to leverage partner solutions to solve customer needs.
- Experience leading a matrixed team without direct management responsibility.
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Responsibilities
We are looking for a Machine Learning Lead – Azure Infrastructure Workload to join our Global Black Belt team to help us accelerate market adoption of AI with strategic customer projects. As the Specialist on the Global Black Belt team, you will be joining a team of highly skilled individuals across the company who are driving the most strategic and innovative customer projects. This role is a senior sales lead within our enterprise sales organization focused on driving customer digital transformation scenarios with the Azure AI platform (inclusive of strategic AI partner solutions).
The Machine Learning Lead – Azure Infrastructure Workload will accelerate and scale Microsoft’s share of the AI market with Azure AI solutions driving cloud consumption. You will partner closely with our mainstream solution sellers, and key partner stakeholders to accelerate AI engagements with our customers.
Being part of the AI Global Black Belt team, you will maintain and develop deep professional, sales and industry thought leadership in AI. You will have opportunities to showcase your expertise at various Microsoft and Industry conferences and work directly with our product engineering teams to influence the evolution of our AI technologies.
