AI/ML Engineer

Location: Bulgaria, Poland, or Romania; work from the European Union region and a valid work permit are required.

Company

hirify.global is a global AI-first digital transformation and engineering partner delivering scalable products, platforms, data solutions, and AI systems.

What you will do

• Design and develop machine learning solutions aligned with business objectives.
• Build, train, evaluate, and deploy models for predictive analytics, recommendation systems, document intelligence, and decision-support use cases.
• Own the ML lifecycle, including data preparation, feature engineering, training, evaluation, deployment, monitoring, and retraining.
• Collaborate with Data Engineers, MLOps Engineers, Solution Architects, and business stakeholders on production-ready solutions.
• Support CI/CD, observability, model governance, technical documentation, and responsible AI practices.
• Troubleshoot production issues and continuously improve existing AI solutions.

Requirements

• Work from the European Union region and a valid work permit are required.
• 3–6 years of professional experience in Machine Learning or AI Engineering.
• Strong Python skills and hands-on experience with PyTorch and/or TensorFlow and scikit-learn.
• Experience building and deploying machine learning models in production environments.
• Experience with MLflow, cloud-based ML platforms, CI/CD concepts, and MLOps practices.
• Strong analytical, problem-solving, communication, and cross-functional collaboration skills.

Nice to have

• Experience with Generative AI, LLM applications, vector databases, embedding models, or RAG architectures.
• Experience with document intelligence, OCR, Azure OpenAI, or advanced deployment strategies.
• Experience in automotive, mobility, retail, dealer-network, or regulated environments.

Culture & Benefits

• Work in a cross-functional Agile environment with Data Engineers, MLOps Engineers, Solution Architects, and business stakeholders.
• Contribute to knowledge sharing and the development of AI/ML capabilities.
• Apply responsible AI principles, governance, transparency, and model documentation practices.
• Work with technologies including AWS, Azure, GCP, Databricks, and Snowflake.

Hiring process

• CV review.
• HR call followed by an interview and client interview.
• Final decision.