Member of Technical Staff - ML Systems & Inference

Gimlet Labs, Inc.; San Francisco (CA); Hybride; USD 150 000 - 390 000; Plein temps

Avantages offerts par ce poste

Equity

Résumé du poste

Gimlet Labs, Inc. is hiring a Member of Technical Staff focused on ML systems in San Francisco, on-site. You will build inference systems that run models end-to-end in production, focusing on batching, scheduling, memory placement, and cross-hardware optimization.

You will collaborate with teams across compilers, kernels, networking, and distributed systems to improve latency, throughput and efficiency of production workloads while enabling new models and accelerators to run at scale.

Qualifications

• Bachelor's degree or equivalent experience in a relevant field.
• Experience building or operating ML inference or model serving systems.
• Ability to reason about latency, throughput and memory under load.
• Proficient in Python and C++ software development.

Responsabilités

• Build and operate end-to-end inference systems in production.
• Optimize batching, scheduling, concurrency, and resource utilization.
• Advance KV cache management and memory placement strategies.
• Collaborate with compiler, kernel, networking, and distributed systems teams.

Connaissances

Strong software engineering

ML inference systems

Performance & memory reasoning

Python & C++ development

Formation

Bachelor's degree in a relevant field

Outils

TensorRT-LLM

vLLM

Custom model serving

Description du poste

# Member of Technical Staff - ML Systems & InferenceResearch & DevelopmentSan Francisco, CAOn-siteFull-time$150K – $390K • Offers EquityApply for this role Application opens on Ashby**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.*