We are seeking an AI Engineer to join a highly technical AI Services team building production-grade GenAI and AI infrastructure products. This role is focused on model optimization, inference performance, AI system design, and enterprise AI deployments, working at the intersection of software engineering, machine learning, and cloud-native infrastructure.
Requirements
- 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
Benefits
- Equipment budget to build your ideal technical workspace
- Company offsites to connect with a highly technical international team
- Career growth within a scaling engineering and AI organization
- Work on cutting-edge distributed systems, AI infrastructure, and production GenAI platforms