Research Engineer - Inference
RemoteFull-timePosted 1mo ago
About the role
Research Engineer focused on deploying and optimizing frontier AI models in production, owning systems that turn research breakthroughs into real-time products used by millions.
Responsibilities
- Deploying state-of-the-art models to production and owning the path from research checkpoint to serving infrastructure.
- Optimizing inference performance across the stack, including latency, throughput, and cost, using techniques such as quantization, distillation, KV-cache optimization, batching strategies, and custom kernels.
- Building and tuning high-performance serving systems for real-time, streaming workloads where every millisecond matters.
- Creating tooling and infrastructure that lets researchers ship new models to production quickly, safely, and with confidence in their performance characteristics.
Qualifications
- Experience deploying and serving ML models in production, ideally for latency-sensitive or real-time applications.
- Strong engineering skills in GPU programming and inference optimization (e.g., CUDA, Triton, TensorRT, or serving frameworks such as vLLM or SGLang).
- Capacity to autonomously profile, diagnose, and eliminate bottlenecks across the serving stack, from model architecture to kernels to orchestration, and to build the tooling to measure it.
Skills
Required:ML model deployment and servingGPU programming and inference optimizationPerformance profiling and bottleneck elimination
Benefits
- Innovative culture
- Growth paths
- Learning & development through an annual discretionary stipend
- Social travel with annual discretionary stipend
- Annual company offsite
- Co-working stipend
Last updated Oct 8, 2026. Interested? Apply on the company site.
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