Full-Time
Member of Technical Staff
ML Systems & Inference
Gimlet Labs
51-200 employees
Serverless AI inference platform with orchestration
Compensation Overview
$150k - $390k/yr
San Francisco, CA, USA
In Person
Bachelor's
 AI & Machine Learning (1) |
|---|
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- Strong software engineering fundamentals.
- Experience building or operating machine learning inference or model serving systems.
- Comfort reasoning about performance, memory usage, and system behavior under load.
- A bachelor's degree in a relevant field, or an equivalent combination of education, training, and professional experience.
- Improve the latency, throughput, and efficiency of production inference workloads.
- Design execution strategies across batching, scheduling, concurrency, and resource utilization.
- Improve key-value cache management, memory efficiency, and execution under load.
- Enable new models, accelerator architectures, and inference techniques to run efficiently in production.
- Build inference systems that execute models end-to-end in production.
- Develop systems that determine how inference executes across the pipeline, including request batching and scheduling, stage placement and scaling, key-value cache and intermediate-state movement between accelerators, and balancing latency, throughput, and utilization across different hardware characteristics.
- Work across model serving, batching, scheduling, concurrency, key-value cache management, and memory placement.
- Bring up models on novel hardware.
- Support new model architectures and inference techniques.
- Improve performance under real production workloads.
- Partner with compiler, kernel, networking, and distributed systems engineers to optimize the full execution path.
- Experience with inference runtimes such as TensorRT-LLM, vLLM, or custom serving systems.
- Deep understanding of modern model architectures and attention mechanisms.
- Experience with batching, scheduling, and concurrency control in inference systems.
- Familiarity with key-value cache management and memory placement strategies.
- Experience profiling and tuning latency- and throughput-critical systems.
- Software development experience in Python and C++.
Gimlet Labs builds an inference cloud platform that runs and coordinates AI agent workloads across heterogeneous hardware, including GPUs and accelerators. It splits workloads and routes tasks to the most suitable hardware to boost throughput without extra cost or power, and offers serverless inference in Gimlet Cloud to let developers scale multi-agent systems while the platform handles scheduling. The company also develops kforge, a toolkit that uses AI agents to automatically generate optimized PyTorch kernels for CUDA, ROCm, and Metal. Its goal is to make AI inference scalable and efficient by hardware-aware orchestration, with options to run in the cloud or on customers' data centers.
Company Size
51-200
Company Stage
Series B
Total Funding
$392M
Headquarters
San Francisco, California
Founded
2023
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Simplify's Take
What believers are saying
- September 4, 2026 Series B raised $300 million at a $3 billion valuation.
- Arm and Microsoft M12 joined September 2026, validating multi-silicon demand.
- March 2026 customer base tripled; October 2025 launch already produced eight-figure revenue.
What critics are saying
- Gimlet plans several hundred megawatts; data-center buildout burns capital before revenue catches up.
- Nvidia, Arm, and hyperscalers can internalize heterogeneous scheduling and crush Gimlet by 2028.
- Customers buying inference optimization from Groq, Cerebras, or in-house teams reduce Gimlet’s pricing power.
What makes Gimlet Labs unique
- Gimlet’s September 2026 platform orchestrates AI workloads across GPUs, CPUs, and accelerators.
- Zain Asgar’s Pixie team brings proven systems expertise from New Relic acquisition experience.
- kforge targets kernel generation across CUDA, ROCm, and Metal, deepening hardware portability.
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Benefits
Flexible Work Hours
Growth & Insights and Company News
6 month growth
↓ -12%1 year growth
↓ -12%2 year growth
↓ -12%2026 funding rounds across biotech, AI and robotics sectors. A roundup of major financing events in biotechnology, artificial intelligence and robotics reported in 2026. Compiled automatically from the sources listed below and checked against Hyperuranios' own capital and research data. Every figure here traces to a linked source. Factual errors reported to the contact address are corrected in the article and noted here. Artificial intelligence. Gimlet Labs announced a $300 million Series B round that lifted its post-money valuation to $3 billion, led by Andreessen Horowitz with participation from Sapphire Ventures, M12, Arm, Menlo Ventures and Factory; the capital will fund expansion of its heterogeneous inference cloud that matches AI workloads to the optimal silicon, a strategy the company says will improve throughput and power efficiency for agentic AI models [2]. San Mateo-based XDOF is in late-stage talks for a Series B valued at roughly $1.2 billion, reportedly led by 8VC, after closing a $70 million Series A three months earlier backed by Thrive Capital, Andreessen Horowitz, Lux Capital, Spark Capital and WndrCo; the startup builds data-pipeline and teleoperation tools that generate physical-world training data for general-purpose robots, a capability it says underpins its rapidly growing $50 million-annual revenue business [4]. An analysis of 2026 venture activity notes that headline-grabbing megarounds in artificial-intelligence firms are inflating overall funding statistics, with North-American AI companies alone accounting for the bulk of the $392 billion reported in the first half of the year, while non-AI startups face a markedly tighter capital environment [6]. Kuwait-based EdTech startup Dawraty raised a $2 million seed round led by Qatar Development Bank to scale its AI-powered bilingual medical-education platform, expand operations in Qatar and deepen commercial partnerships such as a reseller agreement with the Qatar Finance and Business Academy [8]. Italian AI company Cato secured €6 million in a seed round led by Keen Venture Partners, with participation from Vento, Heartfelt, Moonstone, BHeroes, Alecla7, Nova Venture and several angel investors, to further develop its automated public-tender platform, grow its team and extend its services internationally [9]. Robotics. Jaipur Robotics closed a €4.3 million seed round co-led by EquityPitcher Ventures and High-Tech Gründerfonds, with earlier backing from Fondazione Acire, to accelerate international expansion, deepen its computer-vision AI platform for waste-to-energy, cement and biomass plants, and broaden product depth; the company reports hazard-detection accuracy of 99 % and claims over €1 million annual value from improved waste mixing [1][3]. French-based Lupin Dental completed a €15 million Series A for its supervised robotic system that automates minimally invasive tooth preparation for aesthetic veneers; the round was led by Fynveur with a €10 million investment and included Bpifrance and existing shareholders, and the funds will be used to expand partnerships with dental institutions and pursue broader commercial adoption after receiving UKCA certification [5]. Robotics venture capital in 2026 has approached $23 billion, with humanoid-specific funding exceeding $8.6 billion, illustrated by large checks such as Figure AI's $2.34 billion at a $39 billion valuation, Neura Robotics' up-to-$1.4 billion round backed by Nvidia, Amazon, Bosch and Schaeffler, and Apptronik's Series A exceeding $935 million, underscoring a software-style valuation approach to hardware-intensive humanoid firms [7].
United States AI infrastructure company Gimlet Labs raised $300 million in new funding at $3 billion valuation, having raised $80 million in 2026 March, Gimlet Labs founded in 2023 by Zain Asgar, investors include Andreessen Horowitz, Arm & M12. Sep 5, 2026 5th September 2026 | Hong Kong United States AI infrastructure company Gimlet Labs has raised $300 million in new funding at $3 billion valuation, having raised $80 million in 2026 March. Gimlet Labs was founded in 2023 by Zain Asgar. Gimlet Labs investors include Andreessen Horowitz, Arm and M12. Gimlet Labs - Gimlet Labs is an applied research lab dedicated to building next-generation AI infrastructure. "United States AI infrastructure company Gimlet Labs raised $300 million in new funding at $3 billion valuation, having raised $80 million in 2026 March, Gimlet Labs founded in 2023 by Zain Asgar, investors include Andreessen Horowitz, Arm & M12"
Andreessen-backed Gimlet Labs hits $3B valuation with $300M round as AI goes multi-chip. September 4, 2026 * Gimlet Labs raised $300M at a $3B valuation, led by Andreessen Horowitz * The startup's software splits AI workloads across different types of chips * Arm and Microsoft's M12 joined as new backers as Gimlet scales into data centres AI infrastructure is getting harder to build around a single chip. Gimlet Labs, a startup developing software that allows AI workloads to run across different types of chips, has raised $300 million at a $3 billion valuation. The round was led by Andreessen Horowitz, with new backing from Arm Holdings and M12, Microsoft's venture fund. It first raised a $12 million seed round backed by Factory and angels including Intel CEO Lip-Bu Tan, Figma CEO Dylan Field and a16z general partner Raghu Raghuram. Six months later came the $80 million Series A, led by Menlo Ventures and joined by Eclipse, Factory, Prosperity7 and Triatomic. The latest $300 million round takes the company's valuation to $3 billion. The problem Gimlet is trying to solve. Gimlet Labs was co-founded by Zain Asgar, Michelle Nguyen, Omid Azizi, Natalie Serrinoc and James Bartlett. The founding team previously worked together at Pixie, an open-source Kubernetes observability company. Asgar is the CEO; the rest of the team leads engineering, hardware platforms and systems research. Asgar previously founded Pixie Labs, which was acquired by New Relic in 2020. Gimlet started with a relatively simple premise: AI workloads do not necessarily need to run on the same type of chip from start to finish. Its software can divide AI tasks and route different portions to the hardware best suited to them - GPUs for some workloads, CPUs or specialised accelerators for others. The company calls this a multi-silicon inference cloud. Its platform is designed to orchestrate AI workloads across heterogeneous hardware, with Gimlet reporting three-to-ten-times inference speed improvements for the same cost and power envelope. But deploying that software exposed another problem: data centres themselves were largely designed around more homogeneous infrastructure. That has pushed Gimlet beyond software. Asgar said the company is now helping customers configure data centres and is also working on data centres of its own. Different chips can require different cooling systems, temperatures and hardware configurations, turning a software problem into a physical infrastructure problem. From inference software to the data centre. Gimlet is concentrating particularly heavily on AI inference, the stage where trained models generate responses, because Asgar says combining different chips is producing compelling performance gains. That puts the startup in a rapidly expanding market alongside specialised inference players such as Groq and Cerebras. Tech Funding News has covered how Groq's $650 million raise and subsequent $350 million round at a $3.5 billion valuation reflect the growing importance of inference infrastructure, especially after Nvidia's licensing deal reshaped Groq's business. The difference is that Gimlet is not trying to win by designing one superior chip. It is building the software layer that allows multiple architectures to work together. Why a16z is leaning into multi-silicon. For Andreessen Horowitz, Gimlet fits neatly into a much broader shift toward the physical infrastructure underneath AI. On August 31, a16z expanded its Growth fund to $8.5 billion, just days after launching its $1.1 billion Machine Age Fund, which targets chips, memory, networking, storage, data centres and robotics. Its portfolio already includes OpenAI, Databricks, xAI, Mistral, Anduril and SpaceX, alongside newer infrastructure bets. The bigger opportunity for Gimlet may therefore be less about picking the next Nvidia challenger and more about making sure companies do not have to pick just one. If AI infrastructure becomes genuinely multi-silicon, the software coordinating those chips could become infrastructure in its own right.
Gimlet Labs, a startup that helps customers divide artificial intelligence (AI) tasks between multiple types of chips, raised US$300 million in a new round that brought the company’s valuation to...
AI startup Gimlet Labs has raised $300 million in a funding round led by Andreessen Horowitz, valuing the company at $3 billion. New investors include Arm Holdings and M12, Microsoft's venture fund. The startup helps customers distribute AI tasks across different chip types. Gimlet is collaborating with Arm to ensure its software works with various forms of Arm's chip technology. The latest funding comes just six months after Gimlet raised $80 million. Chief Executive Officer Zain Asgar said the round came together quickly due to unsolicited investor interest.