Technology Specialists Machine Learning

This role sits in our Global Black Belt (GBB) organization, which is a team of highly specialized and 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 travel to customer sites.

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 AzureML 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.
- **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.
- **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.

**Qualifications**:
**Required/Minimum Qualifications**:

- 8+ years of technical pre-sales or technical consulting experience
- OR Bachelor's Degree in Computer Science, Information Technology, or related field AND 6+ years of technical pre-sales or technical consulting experience
- OR Master's Degree in Computer Science, Information Technology, or related field AND 4+ years of 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. Technical expert on Azure ML or equivalent compete experience.
- **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.

**Additional or Preferred Qualifications**:

- 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.

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