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TechBiz Global GmbH

Data Scientist

Work from home

Remote role where the employee must remain based in a particular country.

Poland only

Employer listed it 7 weeks ago · Found 5h ago

Been open since 7 weeks ago. Long-running listings are sometimes left up after the role is filled.

Salary

Not stated

Location

Poland only

Timezone

Not stated

Contract

Full-time

Experience

Mid

Category

Data

This employer didn't state pay. Jobs like this usually pay around $110k–$205k a year, a typical range taken from 231 mid-level data roles on Nomaders that do state pay. It's a guide, not an offer.

Remote flexibility

Work from home

This is a remote role, but the employee must be based in Poland. It is work from home rather than work from anywhere.

What the employer says

  • Source listing states candidate location: "Remote job, Krakow, Poland, Krosno, Lublin, Poznan, Warsaw, Remote"
  • Job description states: "based in Poland and able to clearly dem"

What Nomaders makes of it

  • Payroll and tax are likely handled in that country only

The quotes above are the employer's own words; the reading is ours. Always check the original listing and employment terms before working from another country.

About the role

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 process—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.

Proven professional experience as a Data Scientist, Machine Learning Engineer, AI Engineer, or similar role.

Strong hands-on experience training or fine-tuning LLMs and/or SLMs.

Practical experience using GPUs for AI model training.

Strong Python programming skills.

Experience with machine learning and deep-learning frameworks such as:

PyTorch

TensorFlow

Hugging Face Transformers

Experience with GPU-related technologies and environments, such as CUDA, distributed training, cloud GPU platforms, or GPU clusters.

Strong understanding of model-training workflows, including data preparation, tokenisation, model selection, training, evaluation, and optimisation.

Ability to clearly explain previous AI projects, tools used, technical challenges, and achieved results.

Requirements

  • ·Experience with machine learning and deep-learning frameworks such as:
  • ·Hugging Face Transformers
  • ·Experience with GPU-related technologies and environments, such as CUDA, distributed training, cloud GPU platforms, or GPU clusters.
  • ·Strong understanding of model-training workflows, including data preparation, tokenisation, model selection, training, evaluation, and optimisation.
  • ·Ability to clearly explain previous AI projects, tools used, technical challenges, and achieved results.

Benefits

No benefits package published with this listing. Ask about it at first interview.

How to apply

  1. 1Check the flexibility label above, work from home, matches where you plan to live and work.
  2. 2Tailor your CV to the role at TechBiz Global GmbH, mentioning your remote working experience.
  3. 3Apply directly on the employer's careers page using the button below. Nomaders never handles your application.

Found 6h ago. Last checked today. Always confirm the details on the original posting, salary and location can change after publication.

Listing sourced from Company boards.

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