Data Scientist

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.

Job requirements

• 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.
• Experience working with large and complex datasets.
• Good English communication skills.
• Based in Poland.
   

Relevant Industry Experience

Experience in one or more of the following industries or data environments would be highly valuable:

• E-commerce
• Finance or banking
• Insurance
• Healthcare or medical data
• Telemetry and IoT data
• Application or system logs
• Real-time and streaming data

• High-volume enterprise data environments

   

Nice to Have

• Experience with distributed model training.
• Experience with LoRA, QLoRA, PEFT, quantisation, or model compression.
• Experience with MLOps tools and model deployment.
• Knowledge of Docker, Kubernetes, MLflow, or similar technologies.
• Experience using AWS, Azure, or Google Cloud for AI workloads.
• Experience deploying AI models into production environments.
• Knowledge of data privacy, security, and governance requirements.