Lead AI Data Trainer & AI Model Optimization Engineer

We are seeking a Lead AI Data Trainer & AI Model Optimization Engineer to develop, guide, and continuously improve AI models that power intelligent document processing, entity extraction, document classification, and compliance automation solutions. In this role, you will lead the development of training pipelines, training datasets, and model optimization approaches across Small Language Models (SLMs), FastText classifiers, LLM-assisted workflows, and domain-specific extraction engines. You will help define best practices, influence technical direction, and support AI solutions across regulated and data-intensive industries, including Financial Services, Healthcare, Real Estate, Insurance, and Government. This role combines data science, machine learning operations (MLOps), document intelligence, automation engineering, and quality assurance practices to deliver accurate, explainable, and scalable AI solutions in enterprise production environments. • Lead the development, training, evaluation, and optimization of AI models supporting document intelligence, entity extraction, document classification, information retrieval, and compliance automation use cases. • Define and evolve training pipelines, datasets, evaluation frameworks, and automated workflows that support scalable model development and continuous improvement. • Guide the optimization of SLMs, FastText classifiers, LLM-assisted workflows, and hybrid AI extraction solutions to meet customer, business, and operational requirements. • Establish domain intelligence frameworks and best practices that support regulated industries and compliance standards, including GDPR, PCI-DSS, HIPAA, SOC 2, and related requirements. • Define model quality metrics, validation approaches, and performance standards to improve accuracy, explainability, and operational effectiveness. • Analyze production behavior, investigate model performance challenges, and collaborate with Product, Engineering, and Customer Success teams to drive continuous improvement. • Mentor team members, share technical expertise, and contribute to AI engineering standards, documentation, and explainability frameworks. • We are primarily an in-office environment and therefore, you will be expected to work from the Prague office in compliance with Everpure's policies, unless you are on PTO, or work travel, or other approved leave.

• Experience working with NLP, document intelligence, information retrieval, or machine learning systems. • Experience developing, training, evaluating, or optimizing machine learning models, including classification, extraction, retrieval, or LLM-based workflows. • Strong Python development skills and experience working with machine learning frameworks, data processing pipelines, and model evaluation approaches. • Experience with model training, data annotation, dataset management, MLOps practices, or AI lifecycle automation. • Understanding of modern AI technologies such as transformer models, embedding models, SLMs, LLMs, RAG architectures, or prompt engineering techniques. • Experience working with data quality, testing, validation, or model performance measurement frameworks. • Strong analytical, communication, and problem-solving skills, with the ability to collaborate across technical and business teams. • Intelligent Document Processing (IDP) platforms. • OCR, document understanding, semantic search, or enterprise content management systems. • Cloud-based AI platforms such as Azure AI, AWS AI, or Google AI. • Explainable AI frameworks and model governance practices. • Regulated industries and compliance-focused AI solutions. • AI observability, automated testing, vector databases, or production AI operations. #LI-ONSITE