Middle Machine Learning Engineer (AI)

Location: Bulgaria, Hungary, or Poland; in-office, hybrid, or remote flexibility may be available depending on location and contract type.

Company

hirify.global is an AI-first global technology company delivering engineering and digital transformation projects for enterprise clients.

What you will do

• Design and implement end-to-end document intelligence pipelines on AWS.
• Develop and optimize machine learning models for document classification, segmentation, and field extraction.
• Build scalable data processing systems for PDFs of up to 2,000 pages.
• Collaborate with subject matter experts to define and refine extraction requirements.
• Own features from research and proposal through production deployment and monitoring.
• Establish evaluation frameworks and quality metrics for extraction accuracy.

Requirements

• Experience with Python, Pandas, Scikit-learn, TensorFlow or PyTorch, PyStats, and Pydantic.
• Experience with AWS machine learning and deployment tools, including SageMaker, Lambda, CloudFormation or CDK, and Step Functions.
• Advanced knowledge of SQL and data modeling.
• Experience with generative AI for document intelligence, including prompt engineering, RAG, multimodal models, and production deployment through AWS Bedrock or Azure OpenAI APIs.
• Experience with experiment design, including power analysis and hypothesis testing.
• Upper-intermediate English is required, along with clear written and verbal communication for remote and largely asynchronous work.

Nice to have

• Experience with document processing and OCR tools such as AWS Textract or Azure Document Intelligence.
• Experience with PDF and image processing libraries such as PyMuPDF, OpenCV, or Pillow.
• Machine learning and data science experience, including feature engineering, model training, tuning, and supervised or unsupervised learning.
• Experience with AWS big data technologies such as Redshift, S3, EMR, or Glue.

Culture & Benefits

• International projects and collaboration with enterprise clients.
• In-office, hybrid, or remote flexibility depending on location and contract type.
• Medical healthcare, well-being programs, and sports compensation.
• Ongoing learning support and reimbursement.
• Team events, recognition programs, referral bonuses, and local benefits.
• Top-tier equipment provision.