Pragmatike
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Location: Fully remote (EMEA timezone)
Start date: ASAP
Languages: Fluent English required
Industry: AI Infrastructure / Cloud / European Deep-Tech SaaS
Pragmatike is recruiting on behalf of a European deep-tech company building AI-native cloud services and distributed AI infrastructure. Their platform delivers managed inference, LLM-as-a-Service, enterprise RAG solutions, and custom B2B model deployments, supporting real-world production workloads across text, image, and multimodal AI systems.
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.
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.
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
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
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
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
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.
Pragmatike is committed to a fair, transparent, and inclusive recruitment process.
We do not discriminate based on age, disability, gender, gender identity or expression, marital or civil partner status, pregnancy or maternity, race, religion or belief, sex, or sexual orientation.
In accordance with GDPR, your personal data will be processed lawfully, fairly, and securely, and used solely for recruitment purposes, including sharing it with our client(s) for employment consideration. You may request access, correction, or deletion of your data at any time. We are committed to maintaining the confidentiality and security of your information throughout the recruitment process.
Originally posted on Himalayas