Job description

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. Google Research addresses challenges that define the technology of today and tomorrow. From conducting fundamental research to influencing product development, our research teams have the opportunity to impact technology used by billions of people every day. Our teams aspire to make discoveries that impact everyone, and core to our approach is sharing our research and tools to fuel progress in the field -- we publish regularly in academic journals, release projects as open source, and apply research to Google products. Individual pay is determined by factors including job-related skills, experience, and relevant education or training. US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits Learn more about benefits at Google . • Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field. • Design, build, and productionize sophisticated machine learning models to understand user intent and advertiser objectives. Your work will form the core intelligence of our next-generation, AI-driven ad systems. • Collaborate closely with Research Scientists and Product teams to translate novel concepts in LLMs, RL, and agentic systems from initial prototypes into scalable, production-ready solutions. • Take ownership of the end-to-end ML lifecycle to develop and launch new advertising products. Translate into features with significant business impact and shape the future of Google's monetization. • Contribute to the scientific community with opportunities to co-author publications for academic conferences (e.g., NeurIPS, ICML), showcasing your innovative work and its impact. • Bachelor’s degree or equivalent practical experience. • 5 years of experience with software development in one or more programming languages. • 2 years of experience in large language model (LLM) modeling, including pre-training or fine-tuning. • 2 years of experience with Generative AI technologies, and launching features. Minimum qualifications: • Bachelor’s degree or equivalent practical experience. • 5 years of experience with software development in one or more programming languages. • 2 years of experience in large language model (LLM) modeling, including pre-training or fine-tuning. • 2 years of experience with Generative AI technologies, and launching features. Preferred qualifications: • PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field. • 5 years of experience with data structures and algorithms. • Experience driving end-to-end production launches for machine learning features in high-traffic, latency-critical systems. • Experience with Reinforcement Learning (RL) or agentic systems. • Demonstrated publication record at academic conferences (e.g., NeurIPS, ICML, ICLR).

Requirements

Must-haves

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
Learn more about benefits at Google .
Design and implement solutions in one or more specialized ML areas, leverage ML infrastructure, and demonstrate expertise in a chosen field.
Design, build, and productionize sophisticated machine learning models to understand user intent and advertiser objectives. Your work will form the core intelligence of our next-generation, AI-driven ad systems.
Collaborate closely with Research Scientists and Product teams to translate novel concepts in LLMs, RL, and agentic systems from initial prototypes into scalable, production-ready solutions.
Take ownership of the end-to-end ML lifecycle to develop and launch new advertising products. Translate into features with significant business impact and shape the future of Google's monetization.
Contribute to the scientific community with opportunities to co-author publications for academic conferences (e.g., NeurIPS, ICML), showcasing your innovative work and its impact.
Bachelor’s degree or equivalent practical experience.
5 years of experience with software development in one or more programming languages.
2 years of experience in large language model (LLM) modeling, including pre-training or fine-tuning.
2 years of experience with Generative AI technologies, and launching features.
Bachelor’s degree or equivalent practical experience.
5 years of experience with software development in one or more programming languages.
2 years of experience in large language model (LLM) modeling, including pre-training or fine-tuning.
2 years of experience with Generative AI technologies, and launching features.
5 years of experience with data structures and algorithms.

Nice-to-haves

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or related technical field.
Experience driving end-to-end production launches for machine learning features in high-traffic, latency-critical systems.
Experience with Reinforcement Learning (RL) or agentic systems.
Demonstrated publication record at academic conferences (e.g., NeurIPS, ICML, ICLR).

Application prep

Use the role’s language and application details while tailoring your materials.

Keywords to mirror

mlmachine learningaillm

Platform: google
Effort: medium