Minimum qualifications:

• Bachelor’s degree or equivalent practical experience.
• 5 years of experience with software development in one or more programming languages.
• 3 years of experience in AI/ML related engineering.
• 1 year of experience in a technical leadership role with software design and architecture; leading tech design and driving team execution.

Preferred qualifications:

• Master's degree or PhD in Computer Science or a related technical field.
• 5 years of experience with data structures and algorithms.
• Experience in machine learning, building/training AI models, backend data infrastructure or data engineering.
• Experience in developing, deploying, managing, and maintaining machine learning models and infrastructure.
• Understanding of data engineering practices and principles (e.g., tools, processes, pipelines etc.).
• Ability to collaborate with other people, teams across the world and communicate cross-functionally.

About the job

In this role, you will be a key contributor in developing Artificial Intelligence (AI)-motivated capabilities and features for learning products in Search Web and Lens. You will work in close collaboration with product, surface specific engineering and research teams. You will include creating a training dataset, fine-tuning, prompt optimization, evaluating model performance, detecting headroom, launching AI-motivated features and ensuring surface specific quality. You will be involved in designing tech solutions to issues, collaborating with stakeholders and driving delivery.

Responsibilities

• Drive design and implementation of AI features for education in Search Web and Lens.
• Analyze model performance, diagnose loss patterns, and ensure high quality of AI educational user journeys.
• Drive cross-team collaboration with product and surface engineering teams, participate in product initiation, plan timelines and ensure engineering delivery.
• Propose improvements of the team's processes, practices and ensure technical excellence.
• Demonstrate growth mindset, self-reflection, mentor other engineers on the team and share expertise in Artificial Intelligence/Machine Learning (AI/ML) best practices and model development.