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Senior Software Engineer, Generative AI, Google Research

Google

Sunnyvale, CA · HybridJob$174–252K/yrSeen todaySeen in employer's feed today

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At a glance

Compensation
$174–252K/yr
Location
Sunnyvale, CAHybrid
Work Authorization
Not specified

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Job overview

The Senior Software Engineer will design simulation software and AI-driven platforms to model AI workloads on future hardware architectures. The role focuses on performance estimators, agentic workflows, and optimization engines that inform TPU platform roadmaps and hardware decisions. The engineer will work on Google Research’s Performance Simulation team at the intersection of machine learning models and accelerator architecture.

Skills & qualifications

RequiredNice to have

Skills

C++PythonComputer ArchitectureSimulation Software DesignPerformance ModelingScientific ComputingLLM Agentic OrchestrationAutomated Software EngineeringHardware OptimizationCompiler OptimizationSimulation WorkflowsPerformance ProfilingAnalytical Roofline ModelingArchitectural SimulationTransformer ArchitecturesDistributed ExecutionJAXPyTorch/XLAPallasHardware Constraint Analysis

Qualifications

Bachelor's in Computer Science, Computer Engineering, Electrical Engineering or Related Technical Field or Equivalent Practical Experience5 Years Software Engineering ExperienceMaster's or PhD in Computer Science or Related Technical FieldEnglish Proficiency

Full job description

Senior Software Engineer, Generative AI, Google Research

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Experience driving progress, solving problems, and mentoring more junior team members; deeper expertise and applied knowledge within relevant area.

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

Minimum qualifications:

  • 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.

US: $174000 - $252000 (USD) + 15% bonus target + equity + benefits

Learn more aboutbenefits at Google (https://www.google.com/about/careers/applications/benefits/) .

Responsibilities

  • 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.

Information collected and processed as part of your Google Careers profile, and any job applications you choose to submit is subject to Google'sApplicant and Candidate Privacy Policy (./privacy-policy) .

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 alsoGoogle's EEO Policy (https://www.google.com/about/careers/applications/eeo/) ,Know your rights: workplace discrimination is illegal (https://careers.google.com/jobs/dist/legal/EEOC\_KnowYourRights\_10\_20.pdf) ,Belonging at Google (https://about.google/belonging/) , andHow we hire (https://careers.google.com/how-we-hire/) .

If you have a need that requires accommodation, please let us know by completing ourAccommodations for Applicants form (https://goo.gl/forms/aBt6Pu71i1kzpLHe2) .

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.

To all recruitment agencies: Google does not accept agency resumes. Please do not forward resumes to our jobs alias, Google employees, or any other organization location. Google is not responsible for any fees related to unsolicited resumes.

Equity is granted exclusively and discretionarily by Alphabet Inc. on the basis of an agreement concluded between you and Alphabet Inc. Alphabet Inc. is your sole contractual partner with respect to equity grants. GSU grants are not guaranteed, are discretionary, are subject to approval by the Alphabet Inc. board of directors or its delegate, the terms of the relevant Alphabet Inc. stock plan, and your grant agreement. They have no impact on statutory payments. Current or past grants do not confer an acquired right.

Google is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of race, color, ancestry, religion, sex, national origin, sexual orientation, age, citizenship, marital status, disability, gender identity or Veteran status. We also consider qualified applicants regardless of criminal histories, consistent with legal requirements. See also https://careers.google.com/eeo/ and https://careers.google.com/jobs/dist/legal/OFCCP_EEO_Post.pdf If you have a need that requires accommodation, please let us know by completing our Accommodations for Applicants form: https://goo.gl/forms/aBt6Pu71i1kzpLHe2.

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