Description

You will lead the integration and operationalization of machine learning models within the Search area.

This role is on-site.

Responsibilities

• Develop and integrate recommender systems using embedding-based retrieval, reinforcement learning, and transformers.
• Manage machine learning features at scale using Vertex AI Feature Store to ensure consistency and governance.
• Integrate data pipelines into AI workflows using Big Query and Big Table.
• Monitor production ML systems to identify bottlenecks and implement automation for model retraining and deployment.
• Collaborate with data scientists and engineers to assess infrastructure needs, including CPU/GPU resources and networking.

Required Skills

• 5+ years of software engineering experience with a focus on machine learning and MLOps.
• Proficiency in Python, TensorFlow, and PyTorch.
• Expertise in Google Vertex AI and cloud ML platforms.
• Hands-on experience with recommender systems and deep learning frameworks.
• Experience with A/B testing, model evaluation, and optimization techniques.
• Knowledge of Big Query and distributed computing frameworks.
• Understanding of infrastructure requirements for ML deployment, including GPU/CPU scaling.
• Ability to integrate ML models into large-scale applications.

Preferred Skills

• Experience with cloud-native ML tools and MLOps frameworks for lifecycle management.
• Familiarity with scalable feature management and feature store integration.
• Google Cloud or MLOps certifications.

Key Skills

Education

Any Gradute