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KIEFER

Senior ML Engineer, LLM

KIEFER

Senior ML Engineer improving LLM capabilities across European languages at Kiefer Tech. Focused on LLM pre-training, fine-tuning, and model performance in production environments.

Posted 6/22/2026full-timeRemote • 🇵🇱 PolandSeniorWebsite

Tech Stack

Tools & technologies
DockerPythonPyTorch

About the role

Key responsibilities & impact
  • Work on Sophea AI across LLM pre-training, training from scratch, fine-tuning, evaluation, and continuous model improvement
  • Build production-grade ML pipelines for inference, serving, deployment, monitoring, and model lifecycle management
  • Optimize model performance in production, 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

Requirements

What you’ll need
  • Strong hands-on experience with LLMs, including pre-training, training from scratch, 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 language proficiency

Benefits

Comp & perks
  • Compensation: competitive package aligned with talent benchmarks
  • Impact: hands-on role working on Sophea AI, one of the most ambitious Greek-focused AI products in the market
  • Work format: remote work option, with relocation support available for candidates open to working from our Athens office
  • AI-native environment: real challenges across LLMs, training, fine-tuning, inference optimization, GPU workloads, and production AI systems
  • NVIDIA ecosystem: access to related conferences, certifications, internal knowledge sharing, and advanced AI infrastructure through Kiefer’s strategic collaboration
  • Culture: engineering-first, high autonomy, low bureaucracy, and space to build meaningful AI products

ATS Keywords

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Hard Skills & Tools
LLMspre-trainingfine-tuningevaluationperformance improvementML engineeringPythonPyTorchinference optimizationquantization
Soft Skills
ability to build production-grade ML systems