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Member of Technical Staff (Model Quantization & Inference)

NewBe an early applicant On-siteUK

ML engineer/researcher at Lamb Labs developing extreme low-bit (1–2 bit) quantization and inference methods for large language models — covering weight/activation quantization, KV-cache and attention optimization, and QAT/PTQ/distillation — to make models run efficiently on the company's custom AI chip (MPU), working directly with FPGA/ASIC engineers. Core tools: Python and PyTorch.

AI CUDA Fine Tuning FPGA GPU +7 skills

Staff Software Engineer, GPU Inference

Open 88d HybridNorth AmericaStaff

Build and optimize Cerebras' GPU-based AI inference stack, integrating vLLM, ROCm, and AMD GPUs to deliver ultra-low-latency, high-throughput LLM serving for production workloads.

Agentic AI AI API Automation Ccpa +22 skills

Sr. Data Engineer - Services Special Projects

NewBe an early applicant North AmericaSenior

Senior data engineer on Apple's Services Special Projects team building a massive real-time platform that turns multimodal data streams (structured, image, log) into an intelligent, searchable foundation. Day-to-day: designing large-scale ETL/ELT pipelines with Spark, Kafka, Flink and AWS, integrating ML/LLM inference for data enrichment powering Apple services at billions-of-customers scale.

Airflow Analytics AWS Big Data BigQuery +46 skills

Senior Software Engineer, Inference Engine (Platform Software)

Open 66d APACSenior

Build and optimize a high-performance inference engine for LLMs and multimodal models on FuriosaAI’s NPUs, collaborating with compiler and hardware teams to maximize throughput and efficiency.

AI C++ CUDA Deep Learning Generative AI +5 skills

Software Engineer, Compiler (Front-end)

FuriosaAI is seeking a Software Engineer to develop the front-end of their AI compiler, focusing on model ingestion, graph-level optimizations, and the design of a tensor-level kernel language. The role involves translating deep learning models into internal representations and collaborating on compiler infrastructure to maximize performance on AI hardware.

AI C++ Deep Learning GPU LLM +6 skills

Solutions Architect - US

Open 63d North America

Design and deploy AI/LLM models on FuriosaAI’s RNGD NPU using the Furiosa SDK, running POCs, benchmarks, and debugging for US customers while translating technical capabilities into business value.

AI AutoGen Cloud C++ GPU +16 skills

Software Engineer, AI Model Enablement & Inference

Software engineer on FuriosaAI's MLSys team enabling frontier LLMs on the company's NPU chips: analyzing model architectures, writing and optimizing Tensor Contraction Language (TCL) kernels (attention, MoE), integrating models into the Furiosa-LLM inference stack, and validating correctness and performance. Core stack: Python, PyTorch, TCL DSL, with Rust/C++ code reading and vLLM/SGLang technique

AI C++ CUDA LLM Machine Learning +7 skills

Software - Software Engineer, Compiler (Kernel Optimization)

Software engineer on FuriosaAI's compiler team in Seoul who owns the performance of critical AI kernels in Furiosa-LLM: analyzing LLM serving workloads, finding bottlenecks, and writing highly optimized kernels in TCL (Tensor Contraction Language), plus developing scheduling and specialization techniques for dynamic serving workloads.

AI Deep Learning GPU LLM Tcl +1 skills

Staff Machine Learning Engineer, LLM Inference Optimization

NewBe an early applicant Europe, UKStaff Licensed UK sponsor

Staff ML engineer at Nebius Token Factory owning LLM inference optimization end to end: turning model artifacts into fast, reliable, cost-efficient serving endpoints. Day-to-day work spans quantization, speculative decoding, KV-cache tuning, benchmarking harnesses, and engines like vLLM, SGLang, and TensorRT-LLM, built in Python/PyTorch.

Agentic AI AI API Cloud CUDA +10 skills

DevOps / MLOps-инженер (LLM-инфраструктура)

NewBe an early applicant HybridCIS

DevOps/MLOps engineer to own the on-premise infrastructure behind an internal AI services ecosystem: building CI/CD and IaC, managing GPU servers, and deploying and tuning LLM inference on vLLM. Core stack: GitLab CI, Ansible, Docker/Kubernetes, Grafana/Prometheus, Python/Bash, NVIDIA GPU administration.

AI Ansible Argo CD Bash CI/CD +23 skills

Staff AI Product Engineer

Open 38d North AmericaStaff

Staff-level AI engineer setting technical direction for Nscale's GenAI cloud inference platform — dedicated/serverless inference, bring-your-own-model deployments, and post-training services. Deep specialization expected in areas like KV cache/performance, GPU kernels (CUDA/Triton), evals, RL for LLMs, or serving engines (vLLM/SGLang), built on Python, PyTorch, and Kubernetes GPU clusters.

AI API Cloud CUDA DeepSpeed +14 skills

220K – 330K $

Hypercritical.ai

VP of Engineering, Full Stack (CTO Track)

NewBe an early applicant HybridUKFull-timeC-level

About the company We're a frontier AI lab building our own foundation model for safety-critical embedded control software. Think motor controllers, battery management, power electronics and vehicle systems, where a…

AI API AWS Azure CI/CD +19 skills

Principal AI Product Engineer

Open 24d North AmericaPrincipal

Principal-level engineer to own the multi-year roadmap and architecture for Nscale's inference, evals, and post-training platform on its GPU cloud, setting standards that 20-50+ engineers build to. Core work spans GPU kernel efficiency, serving/KV cache architecture, quantization, benchmarking/evals, and RL infrastructure. Salary $290k-$443k USD plus bonus and equity.

AI API Api Design Cloud CUDA +9 skills

290K – 443K $

智能引擎-大模型训练基础架构研发工程师-AI Infra

NewBe an early applicant APAC H-1B sponsor history

AI Infra engineer at Alibaba building distributed training architecture for 100B–1T parameter LLM/multimodal models on multi-thousand-GPU clusters. Daily work: performance analysis, 5D parallelism and communication optimization, hand-written CUDA/Triton operators, XLA/MLIR compiler tuning, and framework-level work in PyTorch/Megatron-LM.

AI C++ CUDA GDB GPU +5 skills

ПАО Сбербанк

Middle AI Infrastructure Engineer

NewBe an early applicant CISMiddle

Scale and maintain Sberbank's production LLM serving infrastructure: keep vLLM/SGLang inference reliable under high load, develop a gateway layer (routing, rate limits, balancing), tune GPU resource allocation and inference parameters, and run deep monitoring and incident response on Kubernetes.

AI CUDA DevOps Docker GPU +9 skills

ПАО Сбербанк

Senior ML Engineer (Kandinsky)

NewBe an early applicant CISSenior

Senior ML Engineer on Sberbank's Kandinsky team researches and trains generative image/video models (diffusion, DiT, VAE), distills and aligns them with RL methods, and builds scalable ML pipelines for automatic data labeling and filtering, using Python, PyTorch, and distributed training (FSDP, DeepSpeed).

AI API DeepSpeed LLM Machine Learning +3 skills

CUDA / AI Engineer

NewBe an early applicant On-siteCIS, Europe, North AmericaContract

An engineer/researcher role focused on optimizing LLM inference on modern GPUs: developing and tuning CUDA kernels, analyzing GPU memory and execution bottlenecks, and benchmarking latency and throughput with frameworks like vLLM, SGLang, and TensorRT-LLM. Deep CUDA/GPU programming and low-level performance debugging skills are central to the day-to-day work.

AI CUDA GPU LLM Machine Learning +6 skills

PyTorch Engineer

Open 133d UK Licensed UK sponsor

About the job Help make Graphcore hardware feel native inside the ML frameworks engineers use every day. As a Software Engineer in our PyTorch team, you will help build the software that connects Graphcore accelerators…

AI C++ Git Machine Learning Python +3 skills

阿里云智能-AI框架与编译器专家-上海

NewBe an early applicant APAC H-1B sponsor history

Alibaba Cloud Intelligence is hiring an AI framework & compiler expert in Shanghai to lead adaptation and optimization of the PyTorch compiler stack for in-house and mainstream AI chips, drive workload-based performance tuning of cloud training/inference, and contribute backends and features to the PyTorch open-source ecosystem. Core tech: PyTorch, Triton, MLIR, TVM.

Silicon Quantum Computing

ML Ops Engineer, Quantum Machine Learning

Build and operate ML pipelines for SQC's quantum-enhanced AI system, Watermelon. You will manage data ingestion, training/evaluation workflows, and experiment tracking while benchmarking quantum features against classical baselines using Python, PyTorch/JAX, and orchestration tools like Airflow or Dagster.

AI Airflow API CI/CD Dagster +24 skills