Develop, train, and refine Computer Vision and NLP models, as well as build powerful LLM agents using Python and PyTorch.
Take ownership of the experimental process by tracking, versioning, and comparing models using MLFlow to ensure the highest quality.
Package and prepare your 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 our systems and help diagnose any logic or behavior issues that arise.

Strong experience with Python and its data processing libraries (Pandas, NumPy).
Practical experience with machine learning frameworks, especially PyTorch .
Knowledge of scikit-learn or spaCy is also valuable.
A 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.
A proactive mindset and the ability to navigate a cloud environment like AWS (e.g., accessing data from S3, running training jobs).
A genuine interest in LLM principles and building agents.
Familiarity with containerization (Docker) and model serving tools (Torchserve, ONNX) is a big plus, as is any experience with GCP.

Health insurance
Additional paid vacation days
Professional growth with funded training, courses, and continuous development programs
Regular team-building events that encourage collaboration

Machine Learning Engineer – Mid-level

Key skills