Software Engineer, Visual Language and Multimodal Modeling

1 Month ago • 2 Years + • Artificial Intelligence • Research & Development

Job Summary

Job Description

Google is seeking a Software Engineer specializing in Visual Language and Multimodal Modeling to develop and deploy industry-leading biometric authentication technology. This role involves exploring multimodal technologies to enhance face authentication, working with data teams to build datasets, identifying and resolving quality issues, implementing and optimizing machine learning algorithms, and integrating them into production systems. Responsibilities include training and evaluating ML models and supporting high-level product area OKRs to accelerate development cycles. The ideal candidate possesses strong software engineering skills (C++, Python), experience with machine learning frameworks (TensorFlow), and a publication record in relevant research areas (CVPR, NeurIPS, etc.). Experience with face anti-spoofing, biometrics, or 3D vision is highly beneficial.
Must have:
  • Bachelor's degree in relevant field
  • 2+ years software development experience
  • Experience with C++, Python, data processing
  • ML algorithm implementation and optimization
  • Publications in CVPR, NeurIPS, etc.
  • Production system development
Good to have:
  • TensorFlow, Flume experience
  • Computer vision libraries/frameworks
  • Android development experience
  • Face anti-spoofing, biometrics expertise
  • 3D/2.5D vision, facial landmark estimation

Job Details


Minimum qualifications:

  • Bachelor's degree in Electrical Engineering, Computer Science, a relevant technical field, or equivalent practical experience.
  • 2 years of experience in software development.
  • Experience in software engineering (e.g., C++, Python, data processing, production backend development, etc.).
  • Experience with publications in related research venues (e.g., CVPR, ICCV, NeurIPS, ICML, ICLR, etc.).

Preferred qualifications:

  • Experience with TensorFlow, Flume, computer vision libraries/frameworks, and Android.
  • Experience in areas like face anti-spoofing, biometrics, 3D/2.5D vision, facial landmark/pose estimation.
  • Ability to build production systems with user impact.
  • Excellent attention to detail and problem solving skills.

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 be responsible for developing, prototyping, and producing industry leading biometric authentication technology. You will support high-level Product Area OKR to develop AI capabilities to accelerate product development cycles.

Google's mission is to organize the world's information and make it universally accessible and useful. Our Devices & Services team combines the best of Google AI, Software, and Hardware to create radically helpful experiences for users. We research, design, and develop new technologies and hardware to make our user's interaction with computing faster, seamless, and more powerful. Whether finding new ways to capture and sense the world around us, advancing form factors, or improving interaction methods, the Devices & Services team is making people's lives better through technology.

Responsibilities

  • Explore with the team multimodal technologies that can improve face authentication solutions, which may include visual language models and multimodal learning techniques.
  • Work with the data team to collect evaluation and training datasets (e.g., define requirements, design data collection system setup, and data labeling programs).
  • Identify quality problems and iterate technical solutions.
  • Design, implement, optimize, and integrate machine learning algorithms into production systems.
  • Train and evaluate Machine Learning (ML) models. 

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