As a Software Engineer, Machine Learning, you will be an integral part of Google’s mission to build innovative solutions that scale and transform how businesses leverage technology. You will contribute to Google Cloud’s rapidly evolving ML infrastructure, playing a key role in designing, implementing, and optimizing machine learning models that impact millions of users worldwide.
At Google, our engineers work on cutting-edge technologies that span various domains, from large-scale distributed systems and cloud computing to AI-driven solutions. As part of the team, you will focus on ML-specific challenges, including improving model efficiency, scalability, and deployment strategies. Whether you're refining speech recognition algorithms, enhancing ML infrastructure, or pioneering advancements in reinforcement learning, your work will drive impactful innovation across industries.
Minimum Qualifications
- Bachelor’s degree in Computer Science, a related technical field, or equivalent practical experience.
- At least 2 years of experience in software development using one or more programming languages such as Python, C++, Java, or Go.
- Strong understanding of data structures and algorithms, with at least 2 years of hands-on experience.
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Minimum of 1 year of experience in at least one of the following domains:
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Speech/audio technology, including voice recognition and synthesis.
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Reinforcement learning, specifically in sequential decision-making tasks.
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Machine Learning (ML) infrastructure, covering model deployment, evaluation, and optimization.
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Any other specialized field within ML.
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1 year of experience working with ML infrastructure components such as data processing pipelines, model debugging, and performance optimization.
Preferred Qualifications
- Master’s or PhD degree in Computer Science, Artificial Intelligence, Machine Learning, or a related field.
- Hands-on experience in developing and optimizing accessible technologies, ensuring inclusivity for users of all abilities.
- Proficiency in designing, implementing, and optimizing large-scale ML models and pipelines.
- Strong problem-solving skills with the ability to analyze complex technical challenges and propose innovative solutions.
About the Role
Key Responsibilities
- Develop and maintain high-quality production-level code for ML models and infrastructure.
- Collaborate with cross-functional teams to refine requirements, conduct code reviews, and implement best practices for efficient and scalable ML solutions.
- Write, update, and maintain documentation and educational content to ensure knowledge transfer and clarity for internal teams and external developers.
- Identify, analyze, and debug complex system issues affecting hardware, networking, or service quality, ensuring the highest level of operational efficiency.
- Work on specialized areas of ML, leveraging state-of-the-art infrastructure to improve model performance, deployment processes, and overall reliability.
Why Join Google Cloud?
Google Cloud is at the forefront of enterprise digital transformation, helping businesses leverage Google’s cutting-edge technologies to solve real-world challenges. With customers spanning 200+ countries and industries, we enable businesses to operate efficiently, securely, and sustainably. As a Software Engineer on our ML team, you’ll have the opportunity to work on high-impact projects, innovate at scale, and shape the future of AI-driven solutions.
How to Apply
If you are passionate about machine learning, eager to push the boundaries of AI, and thrive in a collaborative, fast-paced environment, we encourage you to apply today. Join us in shaping the future of technology at Google Cloud!