20 beste Stellen als technology transfer in zürich, zh – aktuell auf Personalsuche

Bachelor’s degree or equivalent practical experience.
2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
1 year of experience with one or more of the following: Speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), ML infrastructure, or specialization in another ML field.
1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, data processing, debugging).

Preferred qualifications:

Master's degree or PhD in Computer Science or related technical fields.
Experience programming in C++.
Experience with or strong interest in model distillation, knowledge transfer, or teacher-student model architectures.
Experience processing large datasets or fine-tuning models utilizing Large Language Models (Prompting, SFT, RL).
Experience with ML frameworks (e.g., JAX, TensorFlow, or PyTorch) and performance optimization.
Familiarity with search ranking systems, information retrieval metrics, and handling long-tail data distributions.

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.

The team develops models that power web ranking for Google Search. The primary focus is on improving performance for challenging, long-tail queries where traditional signals often fall short. We leverage modeling, experimentation, and scalable engineering to help users find exactly what they are looking for.

In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.

Responsibilities

Design, train, test, and deploy core ranking and machine learning models for Google Search.
Build and maintain data pipelines to transition training data from human ratings to LLM-generated labels, utilizing SFT and RL techniques.
Contribute to model distillation pipelines, helping transfer knowledge from large teacher models to efficient production student models.
Write and maintain model training and large-scale batch processing infrastructure using Python and C++.
Collaborate with peers through design and code reviews, evaluate A/B experiments, and integrate model improvements.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also Google's EEO Policy and EEO is the Law. If you have a disability or special need that requires accommodation, please let us know by completing our Accommodations for Applicants form.

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