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KIEFER

Senior ML Engineer (LLM)

Posted One Month Ago
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Remote or Hybrid
Hiring Remotely in Athens
Senior level
Remote or Hybrid
Hiring Remotely in Athens
Senior level
Develop and continuously improve a Greek-focused large language model across pre-training, training from scratch, fine-tuning, evaluation, and production deployment. Build ML pipelines for inference, serving, monitoring, and lifecycle management, while optimizing latency, throughput, cost, quantization, and GPU utilization. Work with datasets, benchmarks, and experiments to improve model quality and domain performance.
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About the company:

KIEFER is building Greece's integrated AI ecosystem. From renewable energy infrastructure and AI systems to robotics and enterprise applications, we connect the technologies that power Europe's intelligent future. Founded in 2014, KIEFER has delivered 600MW+ of energy projects and is now developing sovereign AI infrastructure, enterprise AI products and physical AI systems for Greece and Southeast Europe.

About the role:

We are looking for a Senior Machine Learning Engineer to join Kiefer Tech and strengthen our ML Engineering team.

In this role, you will work on the development and continuous improvement of Sophea AI, our Greek-focused Large Language Model. You will be deeply involved in LLM pre-training, training from scratch, fine-tuning, model evaluation, inference optimization, and production-grade ML systems.

This is a hands-on engineering role for someone who has already worked directly with language models and understands how to improve their quality, performance, and reliability in real production environments.

Important: this role requires strong practical experience with LLM development. Classical ML, computer vision, basic RAG, or high-level AI tools alone will not be enough for this position.

What you will do:

  • 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

What you will 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

Nice to have:

  • Experience with ASR systems, speech models, or speech-to-text pipelines

  • Experience working with non-English language models, multilingual models, or low-resource language adaptation

  • Experience with MLOps infrastructure, experiment tracking, model serving pipelines, and GPU workload management

  • Contributions to open-source ML projects or published research in AI/ML

What is there for you:

  • 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

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