Senior Software Engineer, AI/ML GenAI, Core

• Write and test product or system development code. 
  
• Collaborate with peers and stakeholders through design and code reviews to ensure best practices amongst available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency,)
  
• Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
  
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.
  
• Design and implement GenAI solutions, leverage ML infrastructure, and evaluate tradeoffs between different techniques and their application domains.
  

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 5 years of experience programming in Python or C++.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  
• 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• 1 year of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).

Preferred qualifications:

• Master's degree or PhD in Computer Science or related technical field.
  
• 5 years of experience with data structures/algorithms.
• 1 year of experience in a technical leadership role.
  
• Experience developing accessible technologies.
  

• Bachelor’s degree or equivalent practical experience.
  
• 5 years of experience programming in Python or C++.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  
• 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
• 1 year of experience with state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision).