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Data Scientist

Role overview

Qualifications

  • Strong hands-on experience in training AI models
  • Experience with Large Language Models (LLMs) and Small Language Models (SLMs)
  • Proficiency in using GPU infrastructure
  • Ability to work with real-world datasets

Responsibilities

  • Train, fine-tune, and optimise LLMs and SLMs using GPU infrastructure
  • Build and manage end-to-end machine learning training pipelines
  • Prepare, clean, structure, and process large volumes of real-world data
  • Collaborate with engineering, data, and business teams to move models from experimentation into production

Key facts

Other skills

  • Collaboration
  • Problem Solving

About the company

TechBiz Global logo

TechBiz Global

IT Services & IT Consulting

TechBiz Global is a leading recruitment and software development company. We provide recruitment, IT outstaffing, outsourcing, software development, and customized consulting services focused on making our clients and partners achieve their recruitment goals successfully. Our service packages are flexible to all sizes of companies and industries. At TechBiz Global, we celebrate diversity and promote an inclusive environment. We work with a diverse set of technologies and frameworks.Β Our international clients and partners extend across more than 20 countries.

Company details

Company typeStartup
IndustryIT Services & IT Consulting
Company size51 - 200

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Job description

At TechBiz Global, we provide recruitment services to top clients from our international portfolio. We are currently looking for a Senior Data Scientist with strong hands-on experience in training AI models, particularly Large Language Models (LLMs) and Small Language Models (SLMs), using GPU infrastructure and real-world datasets.

The ideal candidate should be based in Poland and able to clearly demonstrate their technical expertise, explain the tools and frameworks they use, and describe the complete model-training processβ€”from data preparation to deployment and performance optimisation.

Key Responsibilities

  • Train, fine-tune, and optimise LLMs and SLMs using GPU infrastructure.

  • Build and manage end-to-end machine learning training pipelines.

  • Prepare, clean, structure, and process large volumes of real-world data.

  • Select appropriate models, frameworks, tools, and training approaches based on project requirements.

  • Apply techniques such as supervised fine-tuning, transfer learning, prompt tuning, and parameter-efficient fine-tuning.

  • Monitor model performance and improve accuracy, speed, scalability, and resource utilisation.

  • Work with structured, unstructured, time-series, telemetry, log, and streaming data.

  • Clearly document and explain the tools, methods, and technical decisions used throughout the model-training process.

  • Collaborate with engineering, data, and business teams to move models from experimentation into production.

  • Troubleshoot issues related to model quality, training stability, GPU performance, and data pipelines.

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MR

Marcus Rivera

Chief Revenue Officer

m.rivera@company.com
linkedin.com/in/marcusrivera
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