Senior Staff Software Engineer, Machine Learning, ML Training

• Build and deliver ML frameworks to perform training at LLMS and stable diffusion models for Google Cloud customers.
• Design and implement AI frameworks software for ML workloads in the cloud that enables models for language modeling, stable diffusion, rankings and recommendations, etc.
• Identify and resolve issues in software, performance, and topology.
• Work closely with software engineers, product managers and other engineering teams to get high-quality products and features through the software project lifecycle.
• Design, develop, test, deploy, maintain, and improve software.

Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
  
• 8 years of experience in software development (e.g., Python).
• 7 years of experience leading technical project strategy, ML design, and working with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
  
• 5 years of experience with design and architecture; and testing/launching software products.
  

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or a related technical field.
  
• 8 years of experience with data structures and algorithms.
• 5 years of experience in a technical leadership role leading project teams and setting technical direction.
  
• Experience with ML modeling and scaling.
• Experience with large scale distributed systems or machine learning systems (Training for LLM, image generation).
• Experience with building cloud based services, including with GCP.

• Bachelor’s degree or equivalent practical experience.
  
• 8 years of experience in software development (e.g., Python).
• 7 years of experience leading technical project strategy, ML design, and working with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 5 years of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
  
• 5 years of experience with design and architecture; and testing/launching software products.