Software Engineer III, AI/ML Full-time

Minimum qualifications:

• Bachelor’s degree or foreign equivalent in Computer Science, Engineering, Mathematics, Information Systems, or related field and 2 years of software development experience utilizing C , Python or Java.
• Of the required experience, must have 2 years of experience with data analysis or algorithms.
• Of the required experience, must have 2 years of experience in: Machine Learning tools (TensorFlow, PyTorch, Decision Trees, or Bayesian Networks); Artificial Intelligence (Computer Vision, Expert Systems, or LISP); Natural Language Processing (Generative AI, Large Language Models, Information Retrieval, Computational Linguistics, Optical Character Recognition, Parsing, or Speech Recognition); and, Deep Learning (Neural Networks or Reinforcement Learning).
• Of the required experience, must have 2 years of experience in 3 of the following: Flume; Image Processing; Infrastructure Design; Recommender Systems; Large scale data processing; Language modeling; or, Borg.

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.

The US base salary range for this full-time position is $136,000-$200,000 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 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 about benefits at Google .

Responsibilities

• Design, develop, deploy, optimize and maintain software systems, applications and models to production and integrate them into product offerings involving Artificial Intelligence/Machine Learning (AI/ML) technology by leveraging a deep understanding of the AI/ML hardware and software stack to write product or system development code.
• Find and refine ML model input, utilize ML model output in applications, develop features for ML models, contribute to the ML model algorithm, etc. Conduct testing on code beyond unit testing (e.g. integration, performance, stress, security, load, fuzz), design code to allow for easy testing, and write test case descriptions.
• Review code developed by other engineers and provide feedback to ensure best practices (e.g., style guidelines, checking code in, accuracy, testability, and efficiency). Identify and pay off tech debt to improve long-term maintainability, modifiability, etc.
• Contribute to qualification, end-user documentation, production deployment/monitoring, process automation, and customer support. Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback. Set up or improve test/monitoring/survey infrastructure or processes. Consider code health and system maintainability and scalability over time.
• Triage product or system issues and debug/track/resolve by analyzing the sources of issues and the impact on hardware, network, or service operations and quality.