Hive - AI Engineer

Responsibilities

• 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

Requirements

• 3+ years of software engineering experience with at least 1+ year focused on AI/ML systems
• Hands-on experience with model optimization techniques including quantization, distillation, and fine-tuning
• Strong Python skills and experience with modern ML frameworks (PyTorch, Transformers, diffusers)
• Solid understanding of modern LLM architectures, inference patterns, and GenAI ecosystems
• Experience building real production AI applications (not just research prototypes or notebooks)
• Strong engineering mindset with focus on reliability, scalability, and maintainability
• Ability to move fast while maintaining production-grade quality standards
• Ownership mentality and comfort operating in early-stage, fast-moving environments

Preferred Qualifications

• Experience with computer vision, image/video generation, or multimodal AI systems
• Background in embedding models, vector databases, and semantic retrieval at scale
• Familiarity with structured generation, function calling, agent frameworks, or orchestration systems
• Experience with distributed systems, cloud-native platforms, or AI infrastructure
• Exposure to cost-optimization strategies for large-scale AI inference systems

Benefits

• Fully remote work from anywhere (EMEA timezone preferred)
• 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

About the Company

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.