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Microsoft Senior Applied AI Engineer 
United States, Washington 
318868001

13.08.2024

Required Qualifications:

  • Bachelor's Degree in Computer Science, or related technical discipline AND 4+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python
    • OR equivalent experience
  • Experience in shipping at least one large-scale ML/AI-based service or application, preferably in the security domain on cloud platforms (Azure, AWS, GCP, etc.)
  • Cloud ML and SaaS engineering experience

Other Requirements:

Ability to meet Microsoft, customer and/or government security screening requirements are required for this role. These requirements include, but are not limited to the following specialized security screenings: This position will be required to pass the Microsoft Cloud background check upon hire/transfer and every two years thereafter.

  • Bachelor's Degree in Computer Science or related technical field AND 8+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python

    • OR Master's Degree in Computer Science or related technical field AND 6+ years technical engineering experience with coding in languages including, but not limited to, C, C++, C#, Java, JavaScript, or Python

    • OR equivalent experience.

  • Experience in SecDevOps and MLOps/AIOps.
  • Experience in Python, PyTorch, TensorFlow, or other machine learning frameworks.
  • Experience working with LLMs (Large Language Models) and OSS GenAI (agent-based) frameworks.
  • Experience in at least three of the following: Apache Spark, GraphDBs, VectorDB, Python, LLMs (OpenAI, etc.), C#, Azure and/or AWS APIs and Services.
Responsibilities

1. AI Development and Autonomy:

  • Collaborate with applied research and product teams to develop advanced AI services and automation tools aimed autonomously defending Microsoft. Your work will accelerate detection, containment, investigation, and remediation processes.

2. AIOps System Architecture:

  • Design and implement a scalable AIOps system for experimentation and production environments, ensuring robust and efficient operations.

3. Experimentation:

  • Participate in the development of our AI experimentation and observation platform, driving continuous improvement of AI models and Agentic AI.

4. Cross-Functional Collaboration:

  • Work closely with technical staff from other Microsoft Security products to integrate and enhance security solutions.

5. Technical Design and Innovation:

  • Develop comprehensive technical designs and architectures to transition research innovations into practical, shipping products.

6. Leadership and Collaboration:

  • Foster leadership and collaboration across research and product teams, breaking down silos and driving collective success.
  • Embody our