Machine Learning Engineer (AI)

TL;DR

Machine Learning Engineer (AI): Building and optimizing intelligent models and powerful LLM agents for a global automotive data platform with an accent on model quality, experimentation, and production readiness. Focus on bringing the latest Computer Vision, NLP, and LLM technology to life, ensuring robust, scalable, and deployable systems.

Location: Hybrid work in Vilnius or Kaunas, Lithuania

Salary: 3500-4500 eur/brutto

Company

hirify.global is a data-driven company focused on perfecting how the world buys, owns, and trades vehicles by leveraging automotive data and building the largest online database of used vehicle records.

What you will do

• Develop, train, and refine Computer Vision and NLP models, and build powerful LLM agents using Python and PyTorch.
• Take ownership of the experimental process by tracking, versioning, and comparing models using MLFlow.
• Package and prepare models and agents for production, ensuring they are robust, scalable, and ready for deployment.
• Write clean, maintainable, and well-tested code (Unittest, Pytest) and actively participate in code reviews.
• Work closely with fellow engineers to integrate models into systems and diagnose logic or behavior issues.

Requirements

• Strong experience with Python and its data processing libraries (Pandas, NumPy).
• Practical experience with machine learning frameworks, especially PyTorch.
• Solid understanding of the full machine learning lifecycle, from research and experimentation to production.
• Good command of Git and GitHub for version control and collaborative development.
• Proactive mindset and ability to navigate a cloud environment like AWS (e.g., accessing data from S3, running training jobs).
• Genuine interest in LLM principles and building agents.

Nice to have

• Familiarity with containerization (Docker) and model serving tools (Torchserve, ONNX).
• Experience with GCP.
• Knowledge of scikit-learn or spaCy.

Culture & Benefits

• Work in a data-driven team reshaping the automotive market.
• Real ownership, seeing models move from idea to production.
• Access to a modern ML stack with room to influence technical decisions.
• Dynamic, supportive environment with hybrid work opportunities.
• Professional growth with funded training, courses, and continuous development programs.
• Additional paid vacation days and health insurance.