Machine Learning Lead - Azure Infrastructure Workload

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Qualifications

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.

Solution Area Specialists IC5 - The typical base pay range for this role across the U.S. is USD $130,000 - $217,600 per year. There is a different range applicable to specific work locations, within the San Francisco Bay area and New York City metropolitan area, and the base pay range for this role in those locations is USD $168,600 - $237,500 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here:

Microsoft will accept applications for the role until November 8, 2024.

Microsoft is an equal opportunity employer. All qualified applicants will receive consideration for employment without regard to age, ancestry, color, family or medical care leave, gender identity or expression, genetic information, marital status, medical condition, national origin, physical or mental disability, political affiliation, protected veteran status, race, religion, sex (including pregnancy), sexual orientation, or any other characteristic protected by applicable laws, regulations and ordinances. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. If you need assistance and/or a reasonable accommodation due to a disability during the application or the recruiting process, please send a request via the Accommodation request form .

Benefits/perks listed below may vary depending on the nature of your employment with Microsoft and the country where you work.

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.

As the Machine Learning Lead - Azure Infrastructure Workload on the Global Black Belt team, you will be responsible for:

• Win new AI/ML engagements via technical sales expertise proving technical & business value via workshops (1:1, 1:many) that drive minimum viable product (MVP) for business & technical decision makers showcasing Machine Learning, Cognitive Services and Knowledge Mining capability (60% of your time).
• Accelerate Azure consumption in targeted accounts landing AI/ML engagements by demonstrating technical value of the solution architecture, including best practices for industry application and specialized co-sell solutions that accelerate time to market and customer's digital transformation. (20% of your time).
• Represent the Infra/ML business to leadership
• Define strategy to grow and accelerate Infra/ML PIllar
• Scale technical leadership across mainstream sellers by being the engineering conduit who: champions voice of customer, partner and field to engineering; and prioritizes strategic engineering engagements across customers. (20% of your time).

Solution Skills

• Understanding of analytics and data science processes within organizations and functional stakeholders (ex: data scientists, data engineers, and associated interaction patterns).
• Understanding of a typical development lifecycle and associated operations (Dev Ops, ML Ops) for sustainable enterprise tier installations of cloud architecture.
• Familiarity with core machine learning concepts (ex: compute systems - GPU & FPGA, frameworks - TensorFlow & pyTorch, tools - jupyter notebooks & VS Code, etc.).
• Common understanding of industry or functional scenarios that include machine learning (ex: predictive maintenance, recommendation engines, demand forecasting, knowledge mining, etc.).

Sales Skills

• Sales Leader: Disciplined in business-management, meeting sales targets and operational standards. Mentors other sellers towards a "challenger mentality" by prompting them to engage the customer early with new insights. Demonstrated experience influencing senior stakeholders within customer and own organization.
• Solution Expertise: Deep understanding of unique solution area value, key areas of differentiation, and knowledge to create industry-centric use cases for the solution area.
• Business Value Seller: Proven record of effective account management, particularly demonstrating: coupling business acumen with technology knowledge, to connect customer business challenges to their technology decisions and; coaching the customer through business case creation, approval, and stakeholder buy-in.
• Audience Credibility: Has credibility with key decision makers within our customers. Ability to influence target decision makers such as Business Decision Makers, Operational Technology Leaders, Data Scientist etc.
  Social Seller: Builds an active business network that stretches and influences far beyond themselves, including leveraging social selling tools such as LinkedIn Sales Navigator.
• Excellent Communicator and Collaborator: Relationship building, negotiation, organizational, presentation, written, and verbal communication skills. Ability to effectively collaborate across teams and drive meaningful outcomes with corporate, field, partner and customer stakeholders.
  Technical Acumen: Experienced at driving solutions to full production roll out and solving technical challenges encountered through the project implementation. Synthesizer of tools, services and resources with own expertise to build complete end to end solutions.
• Skill Enablement: A passion for and demonstrated capability of scaling own knowledge with others and building organizational capability in a targeted solution area.

Employers have access to artificial intelligence language tools (“AI”) that help generate and enhance job descriptions and AI may have been used to create this description. The position description has been reviewed for accuracy and Dice believes it to correctly reflect the job opportunity.