Job Description

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 testing, maintaining, or launching software products, and 1 year of experience with software design and architecture.
  
• 3 years of experience with one or more of the following such as speech/audio (e.g., technology duplicating and responding to the human voice), reinforcement learning (e.g., sequential decision making), or specialization in another ML field.
• 3 years of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).

Preferred qualifications:

• Experience in personalization, search, or ranking, with a track record of delivering novel ML solutions.
• Experience leading complex projects and coordinating cross-functional execution between research and infrastructure teams.
• Experience in modern ML frameworks such as TensorFlow, Keras, Jax, or Tflex.
• Proficiency in conducting rigorous, data-driven experimentation to iterate on results and improve product quality.
• Ability to problem solve, commitment to development excellence, and desire to make the world a better place with ML and technologies.

About the job

Google's software developers 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 developer 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 developer, 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 developers 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.

We are building vertex AI search for Commerce, a Google-quality search engine that powers traditional search and agentic discovery experiences for retailers all over the world.

Our quality team is responsible for the quality of the search results which includes query understanding, retrieval quality, relevance modeling, business optimization and personalization. If you are motivated to build scalable, AI solutions and want to define how enterprises leverage self-sustaining systems, join us.

Applied AI builds conversational agents deployed at a large scale that achieve very meaningful results in the real world. Some examples include the customer agent built for large call center environments, to fast food ordering handled by our Food AI agent. The team is transforming how enterprises connect with customers through the power of AI. We also offer unique experiences for team members where you get to work directly with the model builders (Google DeepMind / Vertex), learn and work with brilliant AI leaders, and have access to Global 1000 customers via our existing Google Cloud relationships. The opportunity in this space is tremendous.

The Canada base salary range for this full-time position is CAD 182,000-187,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training.

Please note that the compensation details listed in Canada role postings reflect the base salary only, and do not include bonus, equity, or benefits. Learn more about benefits at Google

Responsibilities

• Design and implement solutions in specialized ML areas, leveraging ML infrastructure to train, tune, and deploy ranking, retrieval, and relevance models.
• Tune small language models and implement new data pipelines to introduce innovative features.
• Analyze data to generate quality improvement ideas and conduct rigorous offline and online experiments, using A/B testing to iterate on results.
• Collaborate with ML Infrastructure and Serving Partner teams on the productization of new quality improvements.
• Participate in design and code reviews to ensure best practices and maintain high system reliability and quality.