Senior Software Engineering Manager, Ai/ml Genai, Google Cloud AI

Google Google · Big Tech · Sunnyvale, CA +1

Senior Software Engineering Manager for Google Cloud AI, focusing on GenAI. This role involves leading teams of engineers, setting technical vision and roadmap, overseeing system designs, and driving the strategy for large-scale ML infrastructure optimization and state-of-the-art GenAI solutions. The team addresses AI challenges for various industries, aiming to push AI's state-of-the-art and collaborate with product teams.

What you'd actually do

  1. Set and communicate team priorities that support the broader organization's goals. Align strategy, processes, and decision-making across teams.
  2. Set clear expectations with individuals based on their level and role and aligned to the broader organization's goals. Meet regularly with individuals to discuss performance and development and provide feedback and coaching.
  3. Develop the long-term technical vision and roadmap within, and often beyond, the scope of your teams. Evolve the roadmap to meet anticipated future requirements and infrastructure needs.
  4. Oversee systems designs within the scope of the broader area, and review product or system development code to solve ambiguous problems.
  5. Drive technical project strategy, lead large-scale ML infrastructure optimization, and oversee the design and implementation of state-of-the-art GenAI solutions.

Skills

Required

  • software development in one or more programming languages (e.g., Python, C, C++, Java, JavaScript)
  • leading technical project strategy
  • ML design
  • optimizing industry-scale ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning)
  • technical leadership role
  • people management or team leadership role
  • state of the art GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (language modeling, computer vision)

Nice to have

  • Master’s degree or PhD in Engineering, Computer Science, or a related technical field
  • working in a complex, matrixed organization

What the JD emphasized

  • manage a team of Engineers
  • manage your project goals
  • manage engineers across multiple teams and locations
  • manage a large product budget
  • technical leadership
  • large-scale ML infrastructure optimization
  • state-of-the-art GenAI solutions
  • GenAI techniques
  • LLMs
  • Multi-Modal
  • Large Vision Models

Other signals

  • leading large-scale ML infrastructure optimization
  • oversee the design and implementation of state-of-the-art GenAI solutions
  • manage engineers across multiple teams and locations
  • manage a large product budget
  • oversee the deployment of large-scale projects