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Software Engineer III, ML Pipeline Development, XR

Google
1 day ago
Full-time
On-site
Zürich, ZH

JobsCloseBy Editorial Insights

Google seeks a Software Engineer III in ML Pipeline Development for XR in Zürich, focusing on productionizing advanced models and pipelines for on-device and server deployments, with emphasis on low-power, high-performance hardware and meeting strict power KPIs. The role requires turning prototypes into production-ready assets, building end-to-end pipelines, and delivering robust algorithms that fit within hardware constraints. Ideal candidates have 2 years Python or C++ experience (or 1 year with an advanced degree), 1 year in CV/ML infra, and preferred experience in 3D CV pipelines, on-device and server deployment frameworks, and power breakdown analysis. To apply, tailor your resume to showcase productionization projects, quantifiable efficiency gains, and cross-team collaboration; highlight on-device deployment, hardware KPIs, and end-to-end pipeline leadership.


Minimum qualifications:

  • Bachelor’s degree or equivalent practical experience.
  • 2 years of experience with software development in Python or C++ programming languages, or 1 year of experience with an advanced degree.
  • 1 year of experience with computer vision (e.g., image classification and processing, object detection, visual search), video generation, or signal processing.
  • 1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Preferred qualifications:

  • Experience building and optimizing production-level pipelines for 3D computer vision or machine learning models.
  • Experience with on-device and server-side deployment frameworks.
  • Proficiency in developing and deploying software for low-power, high-performance hardware.
  • Proven ability to perform power breakdown analysis and optimize for strict hardware KPIs.

About the job

Google's software engineers develop the next-generation technologies that change how billions of users connect, explore, and interact with information and one another. Our products need to handle information at massive scale, and extend well beyond web search. We're looking for engineers who bring fresh ideas from all areas, including information retrieval, distributed computing, large-scale system design, networking and data storage, security, artificial intelligence, natural language processing, UI design and mobile; the list goes on and is growing every day. As a software engineer, you will work on a specific project critical to Google’s needs with opportunities to switch teams and projects as you and our fast-paced business grow and evolve. We need our engineers to be versatile, display leadership qualities and be enthusiastic to take on new problems across the full-stack as we continue to push technology forward.

In this role, you will focus on productionization. You will be transforming advanced models and pipelines into production-ready assets. You will be developing robust algorithms and frameworks to complete the end-to-end pipeline for both prototyping and final production, ensuring seamless deployment across on-device and server-based platforms. You will focus on optimization and system delivery; training machine learning models are not a requirement.For decades, the computing revolution has reshaped our world driven by
breakthroughs in compute, connectivity, mobile, and now, AI. Google's XR
team is at the forefront of the next major leap – the convergence of AI and XR. This is more than just new devices – it's about reimagining how we interact with the world around us. We're building a future where
lightweight XR devices like smart glasses and headsets pair with helpful AI to augment human intelligence, offering personalized, conversational, and contextually aware experiences.

Responsibilities

  • Lead the productionization process by preparing models and pipelines for deployment.
  • Develop algorithms and frameworks to support end-to-end pipeline development for on-device and server environments.
  • Optimize system performance specifically for low-power and high-performance hardware constraints.
  • Execute detailed implementations and conduct thorough power breakdown analysis.
  • Ensure the achievement of critical power Key Performance Indicators (KPIs) necessary for the deployment of real-time spatial technologies.