Opis stanowiska

About the Role

AI-native cloud services and distributed AI infrastructure

\n\n

AI Engineer

You will play a key role in building scalable AI services that power real customer workloads, with strong ownership, technical autonomy, and direct impact on production systems.

What Youll Do

Optimize model inference using advanced techniques including quantization (GPTQ, AWQ, GGUF), distillation, pruning, and speculative decoding
Build and integrate GenAI capabilities beyond LLMs, including computer vision, image generation (Stable Diffusion, FLUX), and multimodal models
Design and implement pre-processing and post-processing pipelines, including prompt engineering, structured output parsing, guardrails, and context management
Build RAG systems, embedding pipelines, and semantic retrieval architectures for enterprise AI applications
Drive model selection, benchmarking, and cost/performance trade-off decisions across AI services
Build evaluation frameworks to measure model quality, latency, reliability, and production performance
Build production AI systems that go beyond experimentation and notebooks, focusing on scalability, reliability, and maintainability
Collaborate closely with platform, infrastructure, and product teams to deliver integrated AI services
Contribute to AI platform architecture and long-term technical direction
Participate in the full lifecycle of AI systems, from research and prototyping to production deployment and operations

Why Join Us

Our client is redefining cloud infrastructure through decentralization and advanced automation, offering a sovereign, energy-efficient alternative to hyperscale cloud providers. Youll join a deeply technical environment where architecture matters, performance is critical, and your decisions will directly shape the evolution of a complex, ambitious platform operating at the intersection of distributed systems, networking, and cloud infrastructure.

AI Engineer

Pragmatike