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Mountain View, California, United States · On-site
$147k–$211k/yr
Mid level$26M raised
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Skills: Generative AI, LLMs, System Architecture, Software Quality Assurance, ML Infrastructure
Mountain View, California, United States · On-site
$72/hr–$91/hr
Mid level
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Mountain View, California, United States · On-site
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About Oso Semiconductor Oso Semiconductor is an early-stage fabless semiconductor company developing next-generation mmWave beamforming technology. Founded by UC Berkeley PhDs, our proprietary RFIC architecture delivers …
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Mountain View, California, United States · On-site
Senior$69M raised
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Mountain View, California, United States · On-site
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Software Engineer III, Generative AI, Agentic Ecosystem Platform
Sign up with Clera and we'll reach out the moment a role actually fits you — no more spraying applications into the void.
$147k–$211k/yr
Full-time
bachelor degree, postgraduate degree
Bonus Target, Equity, Benefits
Posted 86d ago
~40 hrs/week
Responsibilities
Design and implement core infrastructure for Agentic Integrations with a focus on MCP Servers. Develop domain-specific features and surface-agnostic code components across Search, Gemini, and Geo platforms.
Requirements
Requires a Bachelor's degree and at least 2 years of experience in software development, GenAI techniques, and large-scale system architecture. Experience with ML infrastructure and software quality assurance is also required.
Full job description
Minimum qualifications:
Bachelor’s degree or equivalent practical experience.
2 years of experience with software development in one or more programming languages, or 1 year of experience with an advanced degree.
2 years of experience with GenAI techniques (e.g., LLMs, Multi-Modal, Large Vision Models) or with GenAI-related concepts (e.g., language modeling Generative AI Agent, AI Algorithms).
2 years of experience designing, scaling, and maintaining large-scale infrastructure or system architectures.
2 years of experience in software quality assurance, testing methodologies, and automation tools.
1 year of experience with ML infrastructure (e.g., model deployment, model evaluation, optimization, data processing, debugging).
Preferred qualifications:
Master's degree or PhD in Computer Science or related technical fields.
Experience building developer-facing platforms, SDKs, or third-party integration frameworks.
Familiarity with LLM orchestration, tool-use (function calling), and agentic workflows. Direct experience with Model Context Protocol (MCP).
Ability to navigate and lead in a complex, cross-PA (Product Area) environment, aligning technical strategies between Search and Gemini teams.
Ability to start in Mountain View by August 2026.
Passion for rapid prototyping and "hill-climbing" to solve for the nuances of specialized vertical domains.
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.
Join the Agentic Ecosystem team and lead the transformation of Google’s AI from an "answer engine" into an "action engine". We leverage the Model Context Protocol (MCP) to connect advanced AI models to external systems.
In Google Search, we're reimagining what it means to search for information – any way and anywhere. To do that, we need to solve complex engineering challenges and expand our infrastructure, while maintaining a universally accessible and useful experience that people around the world rely on. In joining the Search team, you'll have an opportunity to make an impact on billions of people globally.
Individual pay is determined by factors including job-related skills, experience, and relevant education or training.
A problem isn't truly solved until it's solved for all. Googlers build products that help create opportunities for everyone, whether down the street or across the globe. Bring your insight, imagination and a healthy disregard for the impossible. Bring everything that makes you unique. Together, we can build for everyone.
Check out our career opportunities at goo.gle/3DLEokh
Offices: 1600 Amphitheatre Parkway, Mountain View, CA 94043, US · 111 8th Ave, New York, NY 10011, US · Claude Debussylaan 34, Amsterdam, North Holland 1082 MD, NL · Avenida Brigadeiro Faria Lima, 3477, Sao Paulo, SP 04538-133, BR · 51 Breithaupt St, Kitchener, ON N2H 5G5, CA
How much do Science & Research jobs in Mountain View, CA pay?
Based on 319 listings with disclosed salaries, most science & research jobs in Mountain View, CA pay between $146k–$292k per year. Individual offers vary with seniority, company size, and specialization.
How many Science & Research jobs are open in Mountain View, CA right now?
There are currently 355 open science & research positions in Mountain View, CA listed on Clera. New openings are added daily as companies post roles.
Which companies are hiring for Science & Research roles in Mountain View, CA?
Companies currently hiring include Google, Lightmatter, DensityAI, Samsung Research America (SRA), Kodiak, among others. Browse the listings above to see every active employer.
Are there remote or hybrid Science & Research jobs in Mountain View, CA?
Yes — 74 of the 355 open science & research positions offer remote or hybrid work (4 remote, 70 hybrid).
How do I apply for Science & Research jobs in Mountain View, CA?
Each listing links directly to the employer's application page. Apply early — fresh listings get the most recruiter attention in the first two weeks.