Senior ML Engineer, Search Quality & AI Systems

Google LLC; Zürich; Presencial; CHF 150.000 - 190.000; Jornada completa

Descripción de la vacante

Google LLC is seeking a Senior Software Engineer for Search Quality to advance ML-driven ranking and evaluation across massive-scale systems. You will influence billions of users by building scalable ML-powered components and collaborating with cross-functional teams to push technology forward.

The role emphasizes end-to-end ML work—from data processing and model deployment to monitoring and optimization—while aligning with product goals and engineering best practices.

Formación

• 5 years of experience with software development in C++ or Python.
• 3 years of experience testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
• 3 years of experience specializing in a machine learning field (e.g., foundational models, ML infrastructure, reinforcement learning, or similar areas).
• 3 years of experience with end-to-end machine learning (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Responsabilidades

• Own projects end-to-end from initial idea to design, analysis, and implementation.
• Collect, analyze and visualize data from various sources to formulate and test hypotheses.
• Design and implement ML systems from training data composition to hyperparameter tuning to post-deployment monitoring and optimizations.
• Understand and build upon latest technologies such as Gemini foundational models using distillation and fine-tuning.

Conocimientos

C++

Python

Testing

Software maintenance

Software design & architecture

Kotlin

Educación

Bachelor’s degree or equivalent practical experience

Descripción del empleo

Google LLC is seeking a Senior Software Engineer for Search Quality to advance ML-driven ranking and evaluation across massive-scale systems. You will influence billions of users by building scalable ML-powered components and collaborating with cross-functional teams to push technology forward.

The role emphasizes end-to-end ML work—from data processing and model deployment to monitoring and optimization—while aligning with product goals and engineering best practices.