Senior ML Engineer (LLM)

Posted 22 Days Ago
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Hiring Remotely in Poland
Remote
Senior level
Artificial Intelligence • Robotics • Energy • Renewable Energy
The Role
Develop and improve Sophea AI’s large language models, including pre-training, fine-tuning, evaluation, inference optimization, and production deployment. Build ML pipelines for serving, monitoring, and lifecycle management while optimizing latency, throughput, cost, quantization, and GPU utilization. Work with multilingual datasets and benchmarks, with a particular focus on Polish-language models. The role requires strong hands-on LLM engineering experience and production ML systems expertise.
Summary Generated by Built In

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 Poland.

In this role, you will work on the development and continuous improvement of Sophea AI, expanding our LLM capabilities across European languages, with a particular focus on Polish. 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 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 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

Nice to have:

  • Pre-training and training experience

  • 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

Skills Required

  • Strong hands-on experience with large language models, including fine-tuning, evaluation, and performance improvement
  • Strong machine learning engineering background
  • Experience with Python
  • Experience with PyTorch
  • Experience with Docker
  • Experience with model serving and inference optimization
  • Experience with quantization and GPU workloads
  • Experience with vLLM, SGLang, NVIDIA Triton, TensorRT, TGI, or similar tools
  • Ability to build production-grade machine learning systems
  • Native-level Polish language proficiency
  • Pre-training and training experience
  • Experience with ASR systems, speech models, or speech-to-text pipelines
  • Experience 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 machine learning projects or published AI/ML research
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The Company
368 Employees
Year Founded: 2014

What We Do

KIEFER is a Greek company building an integrated ecosystem spanning renewable-energy infrastructure and advanced technology. Founded in 2014, it has delivered more than 600 MW of energy projects and is developing sovereign AI infrastructure, enterprise AI products, robotics, and enterprise applications for Greece and Southeast Europe. Its technology arm emphasizes EU-based data sovereignty, intelligent automation, GPU infrastructure, and practical business solutions.

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