---
title: 'Member of Technical Staff - ML Systems & Inference at Gimlet Labs'
canonical: 'https://feeny.ai/job/member-of-technical-staff-ml-systems-inference-gimlet-labs-san-francisco-3evwhsfdmz02'
type: 'job'
last_seen: '2026-09-14'
---

# Member of Technical Staff - ML Systems & Inference at Gimlet Labs

- **Company:** Gimlet Labs
- **Location:** San Francisco, CA
- **Compensation:** $150k–$390k
- **Employment:** full-time
- **Work type:** onsite
- **Posted:** 2026-03-10
- **Last confirmed live:** 2026-09-14
- **Apply:** https://jobs.ashbyhq.com/gimlet/8df5a18f-fb87-4c23-8b8b-efffdace4223

## Job description

## About us

Gimlet is building the first multi-silicon neocloud designed for fast, efficient AI inference. We combine large-scale compute infrastructure with an execution platform that partitions AI workloads and maps each stage to the hardware best suited to run it. We work with foundation labs, hyperscalers, and AI-native companies, giving our team access to technical problems spanning frontier models, production infrastructure, and emerging hardware.

## About the role

As a Member of Technical Staff focused on ML Systems, you will build the inference systems that execute models end-to-end in production. You will work on the systems that determine how inference executes across that pipeline: how requests are batched and scheduled, how stages are placed and scaled, how KV cache and intermediate state move between accelerators, and how the system balances latency, throughput, and utilization across different hardware characteristics. You will work across model serving, batching, scheduling, concurrency, KV cache management, and memory placement. You will help bring up models on novel hardware. You will support new model architectures and inference techniques, improve performance under real production workloads, and partner with compiler, kernel, networking, and distributed systems engineers to optimize the full execution path. What success looks like In the first 12-18 months, you will:

- Improve the latency, throughput, and efficiency of production inference workloads
- Design execution strategies across batching, scheduling, concurrency, and resource utilization
- Improve KV cache management, memory efficiency, and execution under load
- Enable new models, accelerator architectures, and inference techniques to run efficiently in production

You may be a good fit if you have

- Strong software engineering fundamentals
- Experience building or operating ML inference or model serving systems
- Comfort reasoning about performance, memory usage, and system behavior under load
- Bachelor's degree in a relevant field, or an equivalent combination of education, training, and professional experience.

Strong candidates may also have

- 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 KV cache management and memory placement strategies
- Experience profiling and tuning latency- and throughput-critical systems
- Software development experience in Python and C++

Why join now? Gimlet is expanding from its core technology into a production neocloud spanning new hardware, customers, and data centers.

- Solve hard problems.
- Own meaningful work.
- Build for production.
- Help define what’s next.

Agency Policy: Gimlet Labs does not accept unsolicited resumes from recruitment agencies or search firms. Any unsolicited resumes submitted without a signed agreement will be considered the property of Gimlet Labs, and no fees will be paid.

## About Gimlet Labs

## Company Overview
- **One-liner**: Gimlet Labs is an applied research lab building next-generation AI infrastructure, specifically a multi-silicon inference cloud that optimizes and orchestrates AI agent workloads across diverse hardware.
- **Entity Type**: Private (Series A)
- **Headquarters**: San Francisco, California, United States
- **Founded**: Not publicly available
- **Founders**: Zain Asgar (CEO), Michelle Nguyen, Natalie Serrino, Omid Azizi

## Core Business
- **Primary industry**: AI Infrastructure / Software Development
- **Target customers**: Large AI model labs, data centers, and enterprises running complex AI agent workloads (B2B, Enterprise).
- **Mission or purpose statement**: To build next-generation AI infrastructure that makes AI workloads 10x more efficient by intelligently orchestrating them across diverse hardware.

## Products & Services
- **Gimlet Cloud**: A serverless inference platform for AI agents. It allows users to run everything from simple agents to complex multi-agent systems with custom logic and data sources. The platform handles scheduling, orchestration, and optimization across diverse hardware. [gimletlabs.ai](https://gimletlabs.ai/)
- **kforge**: An autonomous kernel generation tool that creates optimized low-level kernels directly from PyTorch. It uses a multi-agent system to explore designs, enforce correctness, and identify the fastest kernels for backends like CUDA, ROCm, and Metal. [gimletlabs.ai](https://gimletlabs.ai/)
- **Multi-Silicon Inference Cloud**: A software layer that allows AI workloads to be simultaneously run across diverse types of hardware (CPUs, GPUs, high-memory systems), splitting work to use the best chip for each portion of the model. [techcrunch.com](https://techcrunch.com/2026/03/23/startup-gimlet-labs-is-solving-the-ai-inference-bottleneck-in-a-surprisingly-elegant-way/)

## Market Standing
- **Valuation/Market Cap**: Not disclosed
- **Key Metric**: Total Funding of $92M (Seed: $12M led by Factory; Series A: $80M led by Menlo Ventures). The company publicly launched with eight-figure revenues (at least $10M). [techcrunch.com](https://techcrunch.com/2026/03/23/startup-gimlet-labs-is-solving-the-ai-inference-bottleneck-in-a-surprisingly-elegant-way/)
- **Notable Investors/Partners**: Menlo Ventures (Series A lead), Factory (Seed lead), Eclipse Ventures, Prosperity7, Triatomic. Angel investors include Sequoia’s Bill Coughran, Stanford Professor Nick McKeown, former VMware CEO Raghu Raghuram, and Intel CEO Lip-Bu Tan. Chip partners include NVIDIA, AMD, Intel, ARM, Cerebras, and d-Matrix. [techcrunch.com](https://techcrunch.com/2026/03/23/startup-gimlet-labs-is-solving-the-ai-inference-bottleneck-in-a-surprisingly-elegant-way/)
- **Growth Signals**: The company publicly launched with eight-figure revenues (at least $10M). Customer base has more than doubled in the last four months, including a major model maker and a large cloud computing company. Headcount has grown 966.7% year-over-year to 25-30 employees. [techcrunch.com](https://techcrunch.com/2026/03/23/startup-gimlet-labs-is-solving-the-ai-inference-bottleneck-in-a-surprisingly-elegant-way/) [linkedin.com](https://www.linkedin.com/company/gimletlabs)

## Competitive Advantages
- **Multi-Silicon Orchestration**: The only platform that can simultaneously run AI workloads across diverse hardware (CPUs, GPUs, high-memory systems), splitting models to use the best chip for each portion. This claims to improve inference speed by 3x-10x for the same cost and power. [techcrunch.com](https://techcrunch.com/2026/03/23/startup-gimlet-labs-is-solving-the-ai-inference-bottleneck-in-a-surprisingly-elegant-way/)
- **Autonomous Kernel Generation (kforge)**: Uses AI agents to automatically generate optimized low-level kernels from PyTorch, supporting CUDA, ROCm, and Metal without manual coding. [gimletlabs.ai](https://gimletlabs.ai/)
- **Deep Research Focus**: As an applied research lab, they are working on cutting-edge problems like universal AI compilers, SLA-aware scheduling, and headless hardware architectures, giving them a long-term technological moat. [gimletlabs.ai](https://gimletlabs.ai/)
- **Strong Founding Team**: Founders have deep expertise in systems and infrastructure, with a prior successful exit (Pixie Labs acquired by New Relic). [techcrunch.com](https://techcrunch.com/2026/03/23/startup-gimlet-labs-is-solving-the-ai-inference-bottleneck-in-a-surprisingly-elegant-way/)

## Strategic Focus
- **Productizing Research**: Translating cutting-edge research (universal AI compilers, autonomous kernel generation) into commercial products like Gimlet Cloud and kforge. [gimletlabs.ai](https://gimletlabs.ai/)
- **Scaling the Multi-Silicon Cloud**: Expanding their inference cloud to serve the largest AI model labs and data centers, with a focus on efficiency and cost reduction. [techcrunch.com](https://techcrunch.com/2026/03/23/startup-gimlet-labs-is-solving-the-ai-inference-bottleneck-in-a-surprisingly-elegant-way/)
- **Talent Acquisition**: Aggressively hiring across AI research, kernel/GPU performance, compilers, distributed systems, and business operations to support rapid growth. [jobs.ashbyhq.com](https://jobs.ashbyhq.com/gimlet)

## Why Work Here
- **Cutting-Edge Research & Engineering**: Work on fundamental AI infrastructure problems—autonomous kernel generation, universal AI compilers, and multi-silicon orchestration—alongside PhD-level researchers and top-tier engineers. [gimletlabs.ai](https://gimletlabs.ai/join_us)
- **High-Growth Environment**: The company has grown nearly 10x in headcount over the past year and is backed by top-tier VCs (Menlo Ventures, Sequoia angels). This is an early-stage opportunity with significant impact. [linkedin.com](https://www.linkedin.com/company/gimletlabs)
- **Fast-Moving Team**: Described as a "fast moving team with both AI research and industry expertise," looking for "builders" who love rapid prototyping. [gimletlabs.ai](https://gimletlabs.ai/join_us)
- **Location**: Based in San Francisco, California. The office is at 255 Potrero Ave. [linkedin.com](https://www.linkedin.com/company/gimletlabs)
- **Culture**: The company values researchers, builders, and strategists. The team includes alumni from Pixie Labs, Amazon, Google, AMD, Intel, and Groq. [linkedin.com](https://www.linkedin.com/company/gimletlabs)

## Sources
1. [gimletlabs.ai](https://gimletlabs.ai/)
2. [gimletlabs.ai/join_us](https://gimletlabs.ai/join_us)
3. [jobs.ashbyhq.com](https://jobs.ashbyhq.com/gimlet)
4. [linkedin.com](https://www.linkedin.com/company/gimletlabs)
5. [techcrunch.com](https://techcrunch.com/2026/03/23/startup-gimlet-labs-is-solving-the-ai-inference-bottleneck-in-a-surprisingly-elegant-way/)

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