Software Engineer III, AI/ML
Content + Source + Freshness • 14 Dec 2025 • 95% confidence
Offer value
High value due to competitive financial compensation and the opportunity to work on pioneering AI/ML technologies.
- Competitive salary: $141,000–$202,000/year.
- Open to innovation in AI/ML fields.
- Excellent prospects for career advancement.
- Requires 2+ years in software development and ML.
Pros
- Participation in advanced AI/ML projects.
- Competitive salary package reflective of industry standards.
- Strong collaboration with cross-functional teams.
Cons
- High expectations due to the advanced nature of work.
- Potentially challenging integration with rapidly evolving tech.
- Work pressures associated with cutting-edge project deadlines.
Who it's for
Mid/Senior • On-site
Good fit
- Software engineers with experience in AI/ML.
- Innovators seeking to influence AI product direction.
- Problem solvers with software development skills.
Not recommended for
- Professionals without experience in Python or ML.
- Candidates needing a defined work structure.
- Individuals disinterested in fast-paced technological advancements.
Motivation fit
Key skills
About the job
Software Engineer III, AI/ML
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Mid
Minimum qualifications:
- Bachelor’s degree or equivalent practical experience.
- 2 years of experience with software development in Python.
- 1 year of experience with Generative AI.
Preferred qualifications:
- Master's degree or PhD in Computer Science or a related technical field.
- 2 years of experience with data structures and algorithms.
- Experience with GoLang programming language.
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.SecLM is an Artificial Intelligence (AI) platform of Gemini that offers added value for security partners and customers building security applications. The platform applies Retrieval-augmented generation (RAG), agentic workflows and grounding, with evaluations incorporating the unsurpassed security intelligence such as Google’s visibility into the threat landscape and Mandiant’s frontline intelligence on vulnerabilities, malware, threat indicators, and behavioral threat actor profiles.Google Cloud accelerates every organization’s ability to digitally transform its business and industry. We deliver enterprise-grade solutions that leverage Google’s cutting-edge technology, and tools that help developers build more sustainably. Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
Responsibilities
- Write product or system development code.
- Collaborate with peers and stakeholders through design and code reviews to ensure best practices among available technologies (e.g., style guidelines, checking code in, accuracy, testability, and efficiency).
- Contribute to existing documentation or educational content and adapt content based on product/program updates and user feedback.
- 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.
- Implement solutions in one or more specialized Machine Learning (ML) areas, utilize ML infrastructure, and contribute to model optimization and data processing.
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