ml engineer for LLM products

KIEFER is building Greece’s integrated AI ecosystem, spanning renewable energy infrastructure, AI systems, robotics, and enterprise applications. Founded in 2014, it has delivered 600MW+ of energy projects and is developing sovereign AI infrastructure, enterprise AI products, and physical AI systems for Greece and Southeast Europe.

• Develop and continuously improve Sophea AI, including LLM training from scratch, fine-tuning, evaluation, and model improvement
• Build production-grade ML pipelines for inference, serving, deployment, monitoring, and model lifecycle management
• Optimize production model performance, including latency, throughput, cost efficiency, quantization, and GPU workload usage
• Work with datasets, experiments, benchmarks, and evaluation methods to improve language model quality and domain-specific performance

• Strong hands-on experience with LLMs, including fine-tuning, evaluation, and performance improvement
• Strong ML engineering background, including Python, PyTorch, Docker, and production ML practices
• Experience with model serving, inference optimization, quantization, GPU workloads, and frameworks such as vLLM, SGLang, NVIDIA Triton, TensorRT, TGI, or similar tools
• Ability to build production-grade ML systems, not only research prototypes, scripts, basic RAG applications, or high-level AI integrations
• Native-level Polish proficiency
• Будет плюсом: pre-training and training experience, ASR systems, speech models or speech-to-text pipelines, non-English or multilingual language models or low-resource language adaptation, MLOps infrastructure, experiment tracking, model serving pipelines, GPU workload management, contributions to open-source ML projects or published AI/ML research

• Competitive compensation package aligned with talent benchmarks
• Remote work option; relocation support is available for candidates open to working from the Athens office
• Hands-on work on Sophea AI, described as one of the most ambitious Greek-focused AI products in the market
• Access to AI-related conferences, certifications, internal knowledge sharing, and advanced AI infrastructure through Kiefer’s strategic collaboration with NVIDIA
• Engineering-first culture, high autonomy, low bureaucracy, and space to build meaningful AI products