Software Engineer III

As a Software Engineer III at Google, you will leverage cutting-edge technologies in the AI/ML space to design, implement, and optimize systems that power Google Cloud products. This role requires expertise in machine learning, reinforcement learning, speech/audio technologies, and ML infrastructure. You'll have the opportunity to work with large-scale systems and contribute to Google Cloud's mission of helping organizations digitally transform using innovative AI and ML technologies.

Key Responsibilities

1. Product/System Development. Write efficient, maintainable, and scalable code for developing products or systems that solve complex challenges in the AI/ML domain.
2. Collaboration. Work with peers and stakeholders across teams to ensure adherence to best practices in design, code reviews, and product development. Engage in collaborative code reviews to promote quality and consistency.
3. Debugging & Issue Resolution. Troubleshoot and resolve system or product issues by debugging and analyzing sources of failures or inefficiencies across hardware, network, and service operations.
4. AI/ML Solutions. Implement solutions in specialized ML areas such as speech/audio, reinforcement learning, and model optimization. Contribute to ML infrastructure by optimizing models, processing data, and ensuring high-quality deployment of AI models.
5. Documentation & Knowledge Sharing. Contribute to existing documentation, educational content, and user feedback-based updates. Ensure proper documentation of algorithms, models, and processes for easy understanding and adoption across teams.
6. Innovation. Contribute fresh ideas to solve new challenges and keep pushing the boundaries of AI/ML and cloud computing.

Required Qualifications

• Bachelor’s Degree in Computer Science or related technical fields, or equivalent practical experience.
• At least 2 years of experience in software development with proficiency in one or more programming languages such as Python, Java, or C++.
• 2 years of experience with data structures and algorithms, demonstrating a strong foundation in software engineering and problem-solving.
• 1 year of experience in machine learning (ML) fields, including expertise in reinforcement learning, speech/audio technologies, or ML infrastructure.
• 1 year of experience with ML infrastructure: deployment, model optimization, model evaluation, data processing, and debugging.
• Proven experience in scalable system design and working with large-scale datasets.

Preferred Qualifications

• Master’s Degree or PhD in Computer Science, Artificial Intelligence, or related technical fields.
• Experience developing accessible technologies to ensure products and services are usable by diverse user groups.
• Strong knowledge of ML frameworks such as TensorFlow, PyTorch, or Keras for model development and deployment.
• Familiarity with cloud platforms such as Google Cloud, AWS, or Azure, particularly in implementing AI/ML solutions at scale.
• Experience with distributed computing systems and algorithms that enable efficient processing of massive datasets.
• Leadership skills. Ability to take ownership of projects, mentor junior engineers, and drive technical excellence in a collaborative environment.

Technical Skills & Expertise

1. Programming Languages. Expertise in Python, Java, C++, or other relevant languages for ML systems development.
2. Machine Learning. Experience with supervised, unsupervised, and reinforcement learning algorithms, along with deep learning techniques for solving real-world problems.
3. AI/ML Tools & Libraries. Proficient with TensorFlow, PyTorch, scikit-learn, Keras, and other industry-standard ML frameworks.
4. Cloud Computing. Strong understanding of cloud-based infrastructure and deployment, particularly with Google Cloud or other major cloud platforms like AWS and Azure.
5. ML Infrastructure. Deep knowledge of ML infrastructure components, including model deployment, data pipeline construction, model versioning, and model evaluation.
6. Data Processing. Experience with large-scale data processing, including knowledge of Apache Spark, Apache Kafka, or similar tools for distributed data systems.
7. Software Engineering Principles. Expertise in data structures, algorithms, and software design patterns to build scalable and efficient software solutions.

Personal Attributes

1. Versatility. Adapt quickly to new challenges and projects, with a willingness to learn and contribute to a wide range of areas in AI, ML, and cloud computing.
2. Problem-Solving Skills. Ability to break down complex problems and solve them through systematic, algorithmic thinking.
3. Collaboration. Effective communicator who enjoys collaborating with cross-functional teams to deliver high-quality solutions.
4. Leadership. Ability to provide mentorship, guide junior engineers, and contribute to creating a positive, inclusive team culture.
5. Innovative Thinking. Passionate about AI/ML technologies and staying up-to-date with the latest advancements in the field.

Why Google Cloud? Google Cloud accelerates every organization’s ability to digitally transform by delivering enterprise-grade solutions built on Google’s state-of-the-art technology. As part of the AI/ML team at Google Cloud, you will contribute to innovative solutions that have a massive impact on global businesses. Join a fast-paced, dynamic environment where you will have the opportunity to work on some of the most exciting and challenging problems in AI/ML, all while driving forward Google’s mission to organize the world’s information and make it universally accessible and useful.