Technical Program Manager GeminiApp Automation @ Google DeepMind
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Job Details
Overview
The Technical Program Manager GeminiApp Automation at Google DeepMind is a key role on the Gemini App team, working in a high-velocity startup mindset environment on a top Google priority in conversational AI.
About Google DeepMind
Google DeepMind is a team of scientists, engineers, and machine learning experts dedicated to advancing artificial intelligence for public benefit and scientific discovery. The commitment to safety, ethics, and diversity of thought propels innovative projects forward.
Role Description
As a Technical Program Manager on the Gemini App team, you will:
- Lead development and integration of consumer-facing features in conversational AI.
- Drive initiatives that train models to utilize APIs and deliver contextually relevant responses.
- Collaborate closely with cross-functional teams including Engineering, PM, UX, Legal, Marketing, and more.
- Manage multiple, time-sensitive projects from conception to delivery.
- Identify and mitigate risks, resolving complex dependencies across diverse workstreams.
About You
The ideal candidate has 8+ years of experience in program management with a technical background in ML, LLMs, and MLOps, has thrived in fast-paced startup environments, and possesses a proven track record in launching consumer features through frontend or backend development.
Compensation & Application
This full-time position offers a competitive US base salary range between $183,000 USD - $271,000 USD plus bonus, equity, and additional benefits. Application deadline is 12pm GMT Thursday 7th October 2025. Offers are contingent on a background check.
Key skills/competency
Technical Program Management, Conversational AI, Machine Learning, LLM, MLOps, Cross-functional Leadership, Startup Mindset, API Integration, Risk Mitigation, Project Delivery
How to Get Hired at Google DeepMind
🎯 Tips for Getting Hired
- Customize Your Resume: Tailor skills and accomplishments for Google DeepMind.
- Highlight AI Experience: Emphasize ML, LLMs, and MLOps expertise.
- Research DeepMind: Understand company culture and innovative projects.
- Prepare for Ambiguity: Be ready to discuss handling complex projects.