Staff Team Lead, Google Research

Key Skills

Aartificial intelligence, C Programming, C++, Computer Vision (CV), Java Programming, Large Language Models - LLMs, Leadership, Machine learning techniques, Python Programming, Reinforcement Learning, Video Toolbox

Job Description

Minimum qualifications:

• Bachelor's degree or equivalent practical experience.

• 8 years of experience in software development, and with data structures/algorithms.

• 5 years of experience testing, and launching software products, and 3 years of experience with software design and architecture.

• Experience with ML and one or more of the following: Language, Audio, or LLMs.

Preferred qualifications:

• Master’s degree or PhD in Engineering, Computer Science, or related technical field.

• 5 years of experience in research with sequential modeling or generative AI, deep learning architectures, and Transformers.

• 3 years of experience in a technical leadership role leading project teams and setting technical direction.

• 3 years of experience working in a complex, matrixed organization involving cross-functional or cross-business projects.

• 2 years of experience in a technical Leadership role, contributions to research communities/efforts, including publishing papers in scientific journals or conferences.

• Programming experience in C/C++, Java, Python, computer vision, self-supervised learning, transfer learning, and reinforcement learning.

About the job

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.

In this role, you will be a founding member, lead of this team, and the initial work will be to define the path forward in this challenging space. You will lead a team to conduct independent research and implement systems for multimodal modeling across ambient sensing, device sensing, audio, vision, digital signals, and joint training with Large Language Models (LLM).

Google Research is building the next generation of intelligent systems for all Google products. To achieve this, we’re working on projects that utilize the latest computer science techniques developed by skilled software engineers and research scientists. Google Research teams collaborate closely with other teams across Google, maintaining the flexibility and versatility required to adapt new projects and foci that meet the demands of the world's fast-paced business needs.

The US base salary range for this full-time position is $185,000-$283,000 + bonus + equity + benefits. Our salary ranges are determined by role, level, and location. The range displayed on each job posting reflects the minimum and maximum target for new hire salaries for the position across all US locations. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Your recruiter can share more about the specific salary range for your preferred location during the hiring process.

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

Responsibilities

• Design, implement, and validate new machine learning techniques for multimodal modeling and integration/joint training with LLMs.

• Collaborate with other LLM experts and researchers working on other modalities. Develop new techniques to scale training data, including but not limited to augmentation, synthetic data generation.

• Set up data and evaluation pipelines for multiple modalities (e.g., sensors, language, vision, audio, etc.). Mentor junior researchers and lead research efforts across multiple teams.

• Deploy models for internal testing, experimentation, and demonstration for real-world use cases and publish research results in academic conference and journal.

• Lead the team technically and contribute to overall strategy. Manage individual projects priorities, deadlines, and deliverables adapting to changes and setbacks.