AI/ML Training Infrastructure Lead

Polluxa, Inc.; Sunnyvale (CA); On-site; USD 190,000 - 270,000; Full time

Job summary

Polluxa, Inc. in Sunnyvale seeks an experienced ML leader to set multi-team priorities and drive the mid-term technical vision for scalable ML infrastructure. You will align across teams, coach leaders, and contribute to system designs while guiding ML deployment strategies.

The role emphasizes leading ML design, optimizing infrastructure, and shaping data processing approaches to deliver reliable, high-performance AI systems across the organization.

Qualifications

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience leading ML design and optimizing ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging, fine tuning).
• 5 years of experience with one or more ML areas such as speech/audio or reinforcement learning, or other ML specialization.
• 3 years of experience in a technical leadership role.
• 2 years of experience in people management or team leadership.

Responsibilities

• Set and communicate team priorities that support the broader organization's goals.
• Set clear expectations with individuals based on their level and role and provide feedback and coaching.
• Develop the mid-term technical vision and roadmap within the scope of multiple teams and evolving infrastructure needs.
• Design and guide system designs within the broader area and contribute code to solve problems.
• Lead the design and implementation of ML solutions, optimize ML infrastructure, and guide data processing strategies.

Skills

Software development

ML design leadership

Model deployment

Data processing

Debugging

Education

Bachelor's degree or equivalent practical experience

Master's degree or PhD in Engineering/CS

Job description

Polluxa, Inc. in Sunnyvale seeks an experienced ML leader to set multi-team priorities and drive the mid-term technical vision for scalable ML infrastructure. You will align across teams, coach leaders, and contribute to system designs while guiding ML deployment strategies.

The role emphasizes leading ML design, optimizing infrastructure, and shaping data processing approaches to deliver reliable, high-performance AI systems across the organization.