Principal Technology Specialist - Machine Learning

Are you passionate about helping customers transform their businesses? Microsoft is at the forefront of this transformation; come and help organizations rethink aspects of their business in a way that sets them and their people up for success.

As a Principal Technology Specialist - Machine Learning (ML), you will be a technical solution specialist within our worldwide Artificial Intelligence (AI) commercial solution area organization working with strategic customers on establishing their AI Strategy. Specifically, you will lead strategic technical customer engagements that will require you to deliver architectural design sessions, pilots for ML Platforms, Proof of concept (PoC) ML model development, developing custom foundational models, and advising on best-practices for Enterprise Machine Learning systems. You’ll create Generative AI-powered applications that are enhanced by the broader AI portfolio, with the goal of demonstrating the value of a business use case for your customers. You will collaborate with a virtual team of technical, partner and consulting resources to advance the decision process and increase the adoption of the Azure and AI services, specifically Machine Learning and AI Infrastructure, within your customer accounts.  You will work within your team as a technical solution specialist to help customers derive value for our enterprise customers through AI engagements. 

This role sits in our Global Black Belt (GBB) organization, which is a team of highly specialized technical professionals within our Microsoft Customer & Partner Solutions organization (MCAPS) who work with customers to enable some of the most complex and innovative solutions, providing differentiated technical leadership and guidance along the way. The AI team within the GBB organization consists of Specialist and Technology experts, who focus on specific domains, industries, and workloads, such as Azure OpenAI Service, Azure AI Services, Application Development and Machine Learning.   

This role will require frequent travel to customer sites within the Atlanta, Georgia area.

Microsoft’s mission is to empower every person and every organization on the planet to achieve more. As employees we come together with a growth mindset, innovate to empower others, and collaborate to realize our shared goals. Each day we build on our values of respect, integrity, and accountability to create a culture of inclusion where everyone can thrive at work and beyond.

Responsibilities

• Winning new Azure AI, AI Infra, and ML engagements via solution expertise proving technical and business value via workshops (1:1, 1: many) that drive commitment for minimum viable product (MVP) for business and technical decision makers showcasing Machine Learning capability. 
• Work with the solution specialist team to identify and qualify business opportunities, understand key customer technical objections, and develop the strategy to resolve technical blockers.
• Provide in-depth ML and Deep Learning expertise to support the technical relationship with Azure customers, including product and solution briefings, creating demos, proof-of-concept work, and partner directly with product management to prioritize solutions impacting customer adoption to Azure Machine Learning and AI optimized infrastructure.
• Recommend integration strategies, enterprise architectures, platforms, and application infrastructure required to successfully implement a complete solution using best practices on Azure AI. This includes end-to-end ML Flow processes leveraging AzureML.
• Support developers, creators, and enterprises to leverage open source and in-house developed ML/Deep Learning models so they can build their own AI products in the future.
• Be a trusted advisor to our top customers, helping them understand and incorporate AI/ML accelerators into their overall cloud strategy by recommending migration paths, integration strategies, and application architecture that incorporate Azure AI optimized infrastructure.
• Demonstrate how Azure Machine Learning is differentiated, highlighting the power of accelerators by working with customers on POCs, demonstrating features, optimizing model performance, profiling, and benchmarking.
• Identify and assess large scale ML and Deep Learning opportunities that would benefit from AI optimized infrastructure. You will help customers leverage accelerators within their overall cloud strategy by helping run benchmarks for existing models, finding opportunities to use accelerators for new models, developing migration paths, and helping to analyze cost to performance.  

Other

• Embody our culture and values

Qualifications

Required Qualifications

• 7+ years technical pre-sales or technical consulting experience
  • OR Bachelor's Degree in Computer Science, Information Technology, or related field AND 6+ years technical pre-sales or technical consulting experience
    • OR Master's Degree in Computer Science, Information Technology, or related field AND 4+ years technical pre-sales or technical consulting experience
      • OR equivalent experience.
• AI Experience: 3+ years of AI (Machine Learning, Deep Learning) solution positioning experience in enterprise public cloud-based solutions, working in Azure ML or with a equivalent compete cloud Machine Learning platform.

Preferred Quaifications:

• 8+ years technical pre-sales, technical consulting, or technology delivery, or related experience
  • OR equivalent experience.
• 6+ years experience with cloud and hybrid, or on premises infrastructures, architecture designs, migrations, industry standards, and/or technology management.
• Solution Positioning Experience: 3+ years of experience with managing implementation lifecycle for delivery technology solutions. Work experience should involve presales support, risk management, technical consulting, solution design, project envisioning, planning, development, deployment, and management. Qualified Data Scientist or ML Engineer with proven customer facing consultative skills.
• Experience with AI Models, Large Language Models (LLM), and AI specialized infrastructure especially as it relates to AI trends and issues within businesses. This includes: Open-source models, Hugging Face Hub Community collection and fine-tuning Azure OpenAI Service models.
• Experience with Responsible AI, in practice or theory.
• Familiarity with core machine learning concepts, including infrastructure and open-source options (ex: compute systems - GPU & FPGA, AI/ML frameworks – TensorFlow, MLflow, JAX & PyTorch, tools - Jupyter notebooks & VS Code, etc).
• Certifications with Azure Data, Azure AI or equivalent industry certifications.

Technology Specialists IC5 - The typical base pay range for this role across the U.S. is USD $129,200 - $248,800 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 $162,000 - $268,900 per year.

Certain roles may be eligible for benefits and other compensation. Find additional benefits and pay information here: https://careers.microsoft.com/us/en/us-corporate-pay.

Microsoft will accept applications for the role until October 14, 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.