Tech jobs
Job listings
Senior DevOps LLM (Инвестиционный бизнес)
Senior DevOps engineer builds and scales LLM inference infrastructure for an AI-driven investment platform, deploying open-source models (DeepSeek, Qwen) and optimizing GPU performance with vLLM/TGI.
Software Engineer – Embedded AI (C++) (f/m/div.)
Develop C++ embedded software for AI-powered automotive systems, integrating ML models into occupant monitoring and perception technologies for next-gen vehicles.
Senior AI Solution Architect
Design and deploy enterprise-grade AI systems—from LLMs to robotics—using Python, PyTorch, and MLOps, ensuring scalable, secure, and commercially viable solutions.
AI Engineer (ML Systems & Infrastructure)
Builds and optimizes large-scale AI infrastructure, including Kubernetes clusters, RDMA networking, and GPU orchestration to improve efficiency and scalability of AI training/inference systems.
LLM Inference & GPU Systems Consultant
Optimize and deploy large-scale on-prem LLM inference systems using NVIDIA H200 GPUs, vLLM, TensorRT-LLM, and OpenShift AI for enterprise private GenAI environments.
AI Engineer (Managed Services)
Build and deploy enterprise LLM applications, RAG systems, and AI agents using open-source models (DeepSeek, Qwen, Kimi) and frameworks like LangChain and vLLM.
AI / LLM Inference Engineer
Engineer AI/LLM inference on GPU clusters: benchmark, tune, and optimize model serving with vLLM, Triton, or TensorRT-LLM to hit latency, throughput, and memory targets.
Computer Vision Engineer / Machine Learning Engineer
Research and develop on-device generative and 3D spatial AI models for mobile platforms, optimizing models for edge deployment and shipping to product.
Software Engineer, GPU Cluster Infrastructure
Build and operate a unified GPU compute platform for AI training and inference, hiding cloud complexity behind Kubernetes operators and schedulers that manage multi-cloud NVIDIA clusters.
Senior Forward Deployed Engineer I (AI Infra)
Senior engineer in Bengaluru who partners with AI-native companies to deploy, optimize, and scale production AI systems on DigitalOcean’s AI-Native Cloud, focusing on inference, agentic workloads, and platform tooling.
Data Scientist
Build and deploy ML models for media, ad-tech and e-commerce: recommendations, real-time personalization, pricing and bidding engines that directly lift CTR, eCPM and revenue.
GPU Software Engineer (Graphics / ML)
Build and optimize real-time graphics and ML inference pipelines for interactive visual apps, integrating super-resolution and denoising models into DX12/Vulkan renderers.
Computer Vision engineer
Build and optimize computer-vision services (OCR, detection, classification) in Python, tune models for production, and collaborate with labeling teams and business stakeholders.
Machine Learning Inference Manager
Own and optimize the ML inference platform that powers real-time, near-real-time, and batch predictions for sports data, ensuring low-latency, cost-efficient serving across on-premise GPUs and cloud.
ML Engineer (ML/LLM Ops)
Build and operate ML/LLM platforms for a Korean neobank, focusing on stable, scalable, and secure model training, deployment, and serving using tools like MLflow, Kubeflow, Triton, and vLLM.
Software Developer (Golang & Kubernetes)
Builds and evolves RackAI, a cloud-native AI platform, using Go and Kubernetes to design scalable backend services, operators, and AI-driven tooling while shaping an AI-first engineering culture.
AI Engineer (AMK)
Build and maintain data pipelines for AI systems, integrate ML components, and optimize inference workflows in Python.
Principal AI Engineer
Principal AI Engineer designs and owns the shared AI architecture for multi-agent marketing systems, retrieval pipelines, and evaluation frameworks that power SMB-focused products at scale.
System Software Engineer - Local AI
Build and optimize on-device AI inference software for NVIDIA GPUs, focusing on low-latency, memory efficiency, and deployment on RTX/DGX systems.