科技職缺
職缺列表
Lead NLP / ML Researcher (LLM Evaluation & Agentic Systems)
Lead NLP/ML researcher role at Irisai working remotely on LLM evaluation and agentic systems. The person leads research on model interpretability, RAG evaluation, benchmarking, and uncertainty methods, publishes papers, co-authors grants, and translates research into production prototypes.
AI архитектор
Remote AI architect for international work, leading presales, estimates, solution design, engineer guidance, and deadline control. The role uses Python, FastAPI, Kubernetes, LLMs, GenAI, RAG, AI agents, and CI/CD/DevOps/MLOps; applicants must be outside Russia and Belarus and have at least B2 conversational English.
QA Engineer (LLM-платформа)
QA Engineer at Sber's IT division testing AI products on an internal LLM platform, combining functional/regression testing of LLM features with prompt robustness, evaluation-dataset work, and Python/pytest automation.
Senior LLM Inference Backend Engineer
Design and scale a production GPU-powered LLM inference platform (Nvidia, vLLM, SGLang) serving tens of thousands of users, while also building applied AI products like code assistants, chat, and code-review tools using Python and FastAPI.
[DevOps] DevOps 엔지니어
DevOps Engineer at Coxwave (an AI products company in Seoul) who builds and operates shared cloud infrastructure across multiple AI products, designing CI/CD pipelines, GitOps-based deployment, observability, and secure, cost-efficient AWS (ECS/EKS) environments for both SaaS and on-premise customer deployments.
Senior Full-Stack AI Product Engineer
Senior full-stack engineer building a production AI product end-to-end — React/Next.js frontend, Python/Node backend, real-time voice/video APIs (Tavus, LiveKit, OpenAI Realtime), RAG over PDFs, and deployment on managed platforms like Vercel or Fly.io.
Senior Data Scientist / AI Researcher
Senior data scientist building a multi-agent monitoring platform for AI agents in production at Sberbank. Develops LLM-as-a-Judge evaluators and classical ML models for anomaly detection, degradation forecasting, and root-cause analysis using Python ML and observability stacks.
AI Engineer - Machine Learning
Senior ML Engineer enhancing a client's Databricks data platform with AI capabilities, owning the full ML lifecycle from data through deployment and monitoring. Core stack: Azure AI, Databricks, Python, PySpark, plus modern LLM patterns (RAG, embeddings, agent design).
Senior Data Scientist / AI Researcher
Мы создаем основу для безопасного и эффективного использования ИИ в Банке. Наша команда разрабатывает мультиагентную систему для автономного мониторинга всех ИИ-агентов Банка в промышленной эксплуатации. Это не просто…
Lead Agentic Software Engineer II
Our Deloitte Customer team empowers organizations to build deeper relationships with customers through innovative strategies, advanced analytics, Generative AI, transformative technologies, and creative design. We can…
Cyber Full-Stack Technical Architect/Manager
Deloitte Cyber understands the unique challenges and opportunities businesses face in cybersecurity. Deloitte's Cyber team helps our clients navigate the ever-changing threat landscape. We simplify complexity, and…
Junior Cloud Engineer
MANTECH is seeking a motivated, career and customer-oriented Junior Cloud Engineer to join our team in Springfield, VA . Responsibilities include but are not limited to: Serve our Microsoft Azure customers in executing…
Software Engineering Manager
By clicking the “Apply” button, I understand that my employment application process with Takeda will commence and that the information I provide in my application will be processed in line with Takeda’s Privacy Notice…
AI Engineer
Job Responsibilities Manage and analyse business requirements into a solution design, managing user requirements workshops and formulation of an overall solution design, modelling transactions through the system to…
Software Engineer I, Applied AI Solutions
Hands-on engineering role designing and building production-grade Generative AI, RAG, and agentic workflow solutions for Thermo Fisher Scientific. Uses Python, FastAPI, LLMs (Azure OpenAI, Anthropic Claude), vector stores (PostgreSQL/pgvector, Qdrant), and cloud platforms.