Point your AI agent at freehire and let it find you a job. A CLI and an MCP server over the whole job API — no browser.
Навыки: n8n, Python, vLLM, Qdrant. Квалификация: Middle. Специализации: ML разработчик. ЗАО «Группа компаний С7» (S7 Group) — управляющая компания холдинга S7. Мы занимаемся стратегическим и коммерческим планированием,…
Technical lead for LLM work at Social Discovery Group: speed up and scale LLM inference in production (SGLang, vLLM, distributed multi-GPU/multi-node setups), benchmark GPU hardware, train and fine-tune models, and guide the NLP and CV teams while staying hands-on with PyTorch.
Навыки: Python, FastAPI, Asyncio, NoSQL, CI/CD, Docker, Apache Kafka. Квалификация: Senior. Специализации: Бэкенд разработчик. Проект: Внедрение интеллектуальных модулей на базе ИИ в платформу для автоматизации…
Full stack developer at Umain (the engineering practice of the Eidra UK consultancy) in London who delivers client products using AI coding agents: writing specs, orchestrating parallel agents, and selecting models. Day to day combines spec-driven delivery and agent orchestration with full stack builds in TypeScript, React/Next.js, Node.js/NestJS on cloud (GCP/AWS/Azure) with Terraform.
ADVANCE YOUR CAREER. ADVANCE THE WORLD. At AMD, we believe technology has the power to solve the world’s most important challenges. From advancing healthcare and scientific discovery to powering AI and the technologies…
AI algorithm engineer at Alibaba Group in Hangzhou building LLM agent systems: agent frameworks for retrieval, fact-checking, code-run verification and auto-completion, plus reward/verifier design, expert profiling, and internal benchmarks for RL training. Core stack: PyTorch, HuggingFace, vLLM/SGLang, RLHF/DPO/GRPO.
Senior AI engineer on x1F's internal Corporate IT team, building and operating the company's internal AI platform: making AI applications production-ready, integrating language models with enterprise data, and owning platform decisions. Core stack: Kubernetes/AKS, Azure, Terraform/Bicep, vector databases, Python.
Build and ship AI-powered features end-to-end, turning model capabilities into reliable, real-world user experiences using Python, LLMs, and vector databases.
Designs and ships LLM-powered AI agents for Sberbank's key-clients department: agent architectures (ReAct, tool calling, multi-agent), RAG pipelines, prompt engineering, evals, and production monitoring, packaged as Python/FastAPI services running inside the bank's infrastructure.
AI inference/training optimization expert at Alibaba Cloud Intelligence: tune performance of distributed training and inference engines (PyTorch, DeepSpeed, Megatron, vLLM, SGLang), optimize KV cache, MoE, and PD-disaggregation architectures, and build compilers/kernels with Triton, TileLang, and CUTLASS, including day-0 model support on domestic AI chips.
Senior technical expert at Alibaba Cloud building and optimizing AI infrastructure software for large-model inference services: memory management, GPU memory snapshot/restore, and data-transfer/compute optimization in CPU/GPU heterogeneous environments, plus cross-layer AI framework tuning. Core stack: C/C++/Rust/Python, CUDA, vLLM/SGLang, KVCache and distributed caching.
This position is listed on behalf of a partner company, who manages all applications and next steps. Our partner is looking for a Senior Software Engineer (AI Inference & Runtime Platform) based in the United…
Algorithm engineer at Meituan (Beijing) building LLM and AI Agent capabilities for merchant-facing (B-end) products — intent understanding, task planning, tool use, RAG, Text-to-SQL, multi-agent collaboration, and evaluation systems. Core stack: Python, PyTorch, Transformers, vLLM, faiss.
我们要寻找一位对数据安全和人工智能充满热情的大模型应用算法工程师加入我们的团队。在这里，你将加入一个充满热情的技术团队，参与构建智能化的数据安全防护体系，利用前沿的机器学习与数据挖掘技术，探索大模型在数据安全领域的深度应用。 具体职责包括但不限于： ● 大模型微调与实战 参与开源大模型的后训练（SFT、RL）与效果调优；针对具体的数据安全场景（如敏感词识别、API 风险检测），优化模型推理效果与性能。 ● 数据处理与工程化…
Joins T-Head (Alibaba's AI chip unit) to build and optimize the interconnect/collective communication libraries for its AI chips, enabling efficient multi-GPU/multi-node large-model training and inference. Day to day: C/C++ library development, extreme performance tuning against chip/server/network topology, and diagnosing hangs, crashes, and user issues in large-scale clusters using NCCL/MPI-clas
Build and deploy AI products—query assistants, report summarizers, multi-agent chatbots—for a Vietnamese securities firm (ACBS), using Python, LLM agent frameworks, RAG pipelines, and cloud infrastructure (AWS/GCP).
NVIDIA is at the forefront of the generative AI revolution! The Algorithmic Model Optimization Team focuses on optimizing generative AI models such as large language models (LLMs), vision-language models (VLMs), and…
Apple is looking for a senior software engineer to build the next generation of inference routing for Private Cloud Compute, the backbone of Siri AI and Apple Intelligence. You'll design distributed systems that…
Builds and scales the compute, scheduling, data, and evaluation infrastructure powering RL post-training research on large language models, including LLM inference/training systems, internal tooling, and monitoring/debugging systems. Core stack spans distributed systems on AWS/GCP with Kubernetes, ML frameworks like PyTorch/JAX, and RL training frameworks such as veRL and Ray.
About Us Preference Model is a superintelligence data research company. We build RL environments for training capable, better-aligned superintelligences. Almost every aspect of how a model behaves is shaped by the…
We couldn't check your fit for this role — add a CV to your profile to see it next time.