Senior Software Engineer, Generative AI, Google Research

Google LLC; Sunnyvale (CA); On-site; USD 174,000 - 252,000; Full time

Job summary

Google LLC, Sunnyvale, CA, is seeking a Senior Software Engineer for Generative AI within Google Research. The role focuses on designing and building simulation software and AI-driven platforms to model AI workloads across current and future hardware architectures.

You will contribute to performance estimators, roofline analyses, and toolchains that accelerate hardware/software decisions. The position requires a CS/EE background, 5+ years in software engineering (C++/Python), and strong

Qualifications

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, or related field.
• 5 years of software engineering experience (C++ and Python).
• Experience with computer architecture concepts and performance considerations.

Responsibilities

• Design, build, and maintain scalable performance simulation frameworks for AI workloads and hardware configurations.
• Model how future model architectures interact with architectural variables and memory systems.
• Develop AI-agentic platforms to automate simulator sweeps and parameter sensitivity analyses.
• Build analytical and optimization engines to identify Pareto-optimal execution strategies for hardware and software co-design.
• Provide data-grounded performance projections to guide TPU and hardware roadmaps.

Skills

C++

Python

Software engineering

Computer architecture

Education

Bachelor's degree in CS/CE/EE or related field

Master's or PhD in CS or related field

Tools

JAX

PyTorch/XLA

Pallas

Job description

Senior Software Engineer, Generative AI, Google Research

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corporate_fare Google place Sunnyvale, CA, USA

In most instances, this position requires in-person interviews as part of the hiring process.

• Bachelor's degree in Computer Science, Computer Engineering, Electrical Engineering, a related technical field, or equivalent practical experience.
• 5 years of software engineering (e.g., C++ and Python).
• Experience with computer architecture concepts (memory hierarchies, roofline models, bandwidth versus compute bottlenecks, network topologies).
• Experience with software design for simulation, performance modeling, or scientific computing.

Preferred qualifications:

• Master's degree or PhD in Computer Science, or a related technical field.
• Experience designing LLM-based agentic orchestration loops (e.g., autonomous tool calling, multi-turn reasoning, self-correcting execution) or applying AI to automated software engineering, hardware/compiler optimization, or simulation workflows.
• Experience with performance profiling tools, analytical roofline modeling, or architectural simulators.
• Knowledge of modern transformer architectures (Dense and MoE, long-context attention, speculative decoding) and distributed execution paradigms (SPMD, pipeline, tensor, and expert parallelism) across modern ML frameworks (e.g., JAX, PyTorch/XLA, or Pallas).
• Ability to bridge high-level model specifications with low-level hardware constraints (interconnect latency, SRAM caching, DMA scheduling).

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.

As a Software Engineer on the Performance Simulation team, you will design and develop simulation software and AI-driven platforms that model how AI workloads (e.g., Gemini, MoE thinking/reasoning models, long-context serving) execute on applicant hardware architectures.
Operating at the critical boundary between frontier ML models and future accelerator roadmaps, you will build and automate cycle-level and analytical performance estimators to project throughput, latency SLOs, and Perf/TCO across different silicon configurations (SRAM/HBM hierarchies, multi-dimensional ICI interconnects, optical switching, and specialized compute engines like SparseCore). You will integrate LLM-driven agentic workflows to automate sweep generation, parameter exploration, data retrieval, and bottleneck diagnosis—accelerating hardware/software decisions.

Google Research is building the next generation of intelligent systems for all Google products. To achieve this, we’re working on projects that utilize the latest computer science techniques developed by skilled software developers and research scientists. Google Research teams collaborate closely with other teams across Google, maintaining the flexibility and versatility required to adapt new projects and foci that meet the demands of the world's fast-paced business needs.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

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.

As a Software Engineer on the Performance Simulation team, you will design and develop simulation software and AI-driven platforms that model how AI workloads (e.g., Gemini, MoE thinking/reasoning models, long-context serving) execute on applicant hardware architectures.
Operating at the critical boundary between frontier ML models and future accelerator roadmaps, you will build and automate cycle-level and analytical performance estimators to project throughput, latency SLOs, and Perf/TCO across different silicon configurations (SRAM/HBM hierarchies, multi-dimensional ICI interconnects, optical switching, and specialized compute engines like SparseCore). You will integrate LLM-driven agentic workflows to automate sweep generation, parameter exploration, data extraction over gigabytes of simulation sweeps—reducing analysis cycles from weeks to hours.

Google Research is building the next generation of intelligent systems for all Google products. To achieve this, we’re working on projects that utilize the latest computer science techniques developed by skilled software developers and research scientists. Google Research teams collaborate closely with other teams across Google, maintaining the flexibility and versatility required to adapt new projects and foci that meet the demands of the world's fast-paced business needs.

Individual pay is determined by factors including job-related skills, experience, and relevant education or training.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits
Learn more about benefits at Google .

• Design, build, and maintain scalable performance simulation frameworks to accurately evaluate training and serving metrics for next-generation TPU configurations.
• Model how future model architectures (e.g., Mixture-of-Experts, multi-head latent attention, hybrid sequence parallelism, sparse attention, and KV-cache compression) interact with architectural variables (e.g., SRAM capacity/bandwidth, HBM contention, ICI network topologies, and live failover mechanisms).
• Develop and integrate AI-agentic platforms and toolchains to automate simulator sweep setup, parameter sensitivity analyses, and data extraction over gigabytes of simulation sweeps—reducing analysis cycles from weeks to hours.
• Build analytical and optimization engines (e.g., Mixed-Integer Programming/MIP, simulated annealing, roofline estimation) to identify Pareto-optimal execution strategies (sharding, tensor placement, weight pinning, prefetching).
• Formulate clear, data-grounded performance projections and comparative studies (e.g., Iso-execution analysis, trade-off studies between compute density versus memory bandwidth) to inform multi-year TPU platform roadmaps and hardware contracts.

Google is proud to be an equal opportunity and affirmative action employer. We are committed to building a workforce that is representative of the users we serve, creating a culture of belonging, and providing an equal employment opportunity regardless of race, creed, color, religion, gender, sexual orientation, gender identity/expression, national origin, disability, age, genetic information, veteran status, marital status, pregnancy or related condition (including breastfeeding), expecting or parents-to-be, criminal histories consistent with legal requirements, or any other basis protected by law. See also Google's EEO Policy , Know your rights: workplace discrimination is illegal , Belonging at Google , and How we hire .

Google is a global company and, in order to facilitate efficient collaboration and communication globally, English proficiency is a requirement for all roles unless stated otherwise in the job posting.

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