907 inference jobs at 399 companies in United States
2mo
Save
Mark Applied
Hide
2mo
INFERENCE ENGINEER
San Francisco, California, United States
OnsiteFull Time
MakerMaker: Small San Francis-based AI startup focused on autonomous agents and production ML systems.
3+ YOESenior ML systems engineer with 3+ years building production-grade, large-scale serving infrastructure; strong distributed systems; GPU-accelerated inference; fluent Python and systems languages (C++, CUDA, ROCm or Triton).
Majestic Labs: Developing memory-first AI server platforms for data centers.
3+ YOE3+ years building or operating production LLM inference systems; strong Python and C++; experience with vLLM/SGLang/TensorRT-LLM/Fireworks; distributed inference and performance profiling skills.
vLLM, SGLang, TensorRT-LLM, Fireworks, Python, C++, collective communication library (CCL)
Fuse Energy: Vertically integrated renewable energy supplier and decentralized grid developer.
4+ YOE4+ years building or operating large-scale inference serving systems; deep hands-on experience with inference frameworks and optimisation techniques; systems thinking; experience working with GPU/CUDA engineers; ownership of architecture decisions.
NEAR AI: Building private, verifiable infrastructure for autonomous AI agents.
Expert in LLM inference and serving systems, optimizing throughput/latency/cost for open-source LLMs, deep GPU architecture knowledge, and experience with PyTorch, Triton, CUDA and inference engines like vLLM/SGLang/TensorRT.
SGLang, vLLM, TensorRT, PyTorch, Triton, CuTe, CUDA
NetflixNASDAQ: NFLX: Global video streaming and media production service.
4+ YOE4+ years in ML production/VFX/technical production; hands-on GPU inference for image/video/audio; Python and Linux command-line experience; strong debugging, deep learning inference knowledge, and video format familiarity.
NetflixNASDAQ: NFLX: Provider of global streaming entertainment and video content.
4+ YOE4+ years running GPU-based ML inference or related technical production; hands-on Python/Linux/GPU experience; debugging production runs; knowledge of deep learning inference and video/image formats; strong communication and collaboration skills.
Luma AI: Develops multimodal AI for video generation and creative production.
8+ YOE8+ years in large-scale distributed systems or ML infrastructure; experience operating inference fleets at thousands-of-GPUs scale; technical leadership; Python, PyTorch, Kubernetes; scheduling, queuing, autoscaling, observability, and SLO ownership.
Modular: Unified software infrastructure and programming language for AI development.
5+ YOE5+ years in distributed systems or performance engineering; experience building reusable tooling; strong technical judgment, communication, and leadership; GPU/kernel, inference engine, Kubernetes, and LLM familiarity helpful.
Material: Specialized inference cloud platform for high-performance AI workloads.
BS in CS/EE or related field; proficiency in Rust/Go/Python/C++; knowledge of concurrency, tail latency; experience with model serving; GPU/ASIC programming; low-precision inference; profiling and benchmarking.
d-Matrix: Develops high-performance semiconductor chips for generative AI inference.
10+ YOEBachelor's in CS/EE (or equivalent) with 10+ years experience (Master/PhD with 6+ years preferred); strong Python and C/C++; experience optimizing LLM inference, quantization, batching, GPU kernel programming and contributor-level work on inference frameworks.
Pika: AI-powered platform for generating and editing professional videos
5+ YOE5+ years engineering experience in inference acceleration, GPU programming (CUDA, NCCL), model deployment, quantization, attention optimization, and parallelism for production-scale AI systems.
ZoomNasdaq: ZM: Provides a cloud-based platform for video, voice, and collaboration.
3+ YOEMaster's in CS/EE or related,3+ years in speech recognition or model inference,deep learning expertise,experience with Python,C/C++,CUDA,TensorRT,PyTorch,TensorFlow and GPU optimization.
DigitalOceanNew York Stock Exchange: DOCN: Simplifies cloud infrastructure for developers, startups, and SMBs.
5+ YOE5+ years in high-performance computing or AI infrastructure, deep GPU and low-level optimization expertise, experience with CUDA/Triton/ROCm, distributed GPU parallelization, and system design for inference workloads.
NVIDIANASDAQ: NVDA: Designs GPU-accelerated computing and artificial intelligence hardware.
6+ YOE6+ years industry experience; strong Python and C++; hands-on GPU profiling (CUPTI, NSYS, NCU); experience with LLM inference frameworks and GPU kernel optimization; advanced degree or equivalent experience.
Anyscale: Cloud platform for scaling distributed machine learning applications.
Familiarity with running ML inference at large scale with high throughput and low latency; experience with PyTorch; solid understanding of distributed systems.
NVIDIANASDAQ: NVDA: Designs graphics processing units and artificial intelligence hardware.
6+ YOEMaster's/PhD or equivalent,6+ years industry experience,agentic AI systems experience,strong Python/C++,GPU profiling (CUPTI,NSYS,NCU),LLM inference frameworks,CUDA/CUTLASS/Triton and PTX/SASS familiarity.
Rhoda AI: Developing generalist robotic intelligence for real-world industrial automation.
3+ YOE3+ years in inference optimization, ML systems; strong PyTorch; experience with quantization, pruning, distillation; familiarity with Triton/TensorRT; CUDA knowledge.
Elorian AI: AI lab building multimodal models for advanced visual reasoning.
3+ YOE3+ years building low-latency, high-throughput inference serving systems; knowledge of quantization, batching, speculative decoding, KV cache; experience with vLLM/TensorRT-LLM/Triton/SGLang; multi-GPU model parallelism; C++/CUDA/Python; autoscaling and GPU cost optimization.