Senior AI/ML Engineer

Location: Bulgaria, Poland, or Romania. Work from the European Union region and a 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 across 16 countries.

What you will do

• Lead the design and delivery of complex machine learning and AI solutions aligned with business objectives.
• Define ML architecture standards, development patterns, technology strategies, and engineering best practices.
• Design and oversee end-to-end ML solutions covering data preparation, feature engineering, training, evaluation, deployment, monitoring, and retraining.
• Build and deploy production-grade models using modern ML frameworks and cloud-based platforms.
• Drive CI/CD, observability, model lifecycle management, operational excellence, and production troubleshooting.
• Provide technical leadership, mentor AI/ML Engineers, advise stakeholders, and oversee AI governance and AI Act compliance.

Requirements

• 6+ years of professional experience in Machine Learning or AI Engineering.
• Strong Python programming 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 or similar ML lifecycle management platforms and cloud ML platforms, preferably Azure ML.
• Strong understanding of MLOps, CI/CD, model evaluation, experimentation, monitoring, lifecycle management, and structured and unstructured data.
• Work from the European Union region and a work permit are required.

Nice to have

• Experience with Generative AI, LLM applications, vector databases, embedding models, and RAG architectures.
• Experience with document intelligence, OCR, Azure OpenAI, or regulated AI systems.
• Knowledge of blue/green, canary, rolling, or shadow deployment strategies.
• Experience in automotive, mobility, retail, or dealer-network environments.

Culture & Benefits

• Work with leading technologies including AWS, Azure, GCP, Databricks, and Snowflake.
• Collaborate with Data Engineers, MLOps Engineers, Solution Architects, business stakeholders, and client AI teams.
• Contribute to knowledge sharing, capability building, engineering standards, and continuous improvement.

Hiring process

• CV review, HR call, interview, client interview, and final decision.