Vacancy details
This is a private vacancy. Company details stay confidential until InVault confirms a serious candidate fit.
- Status
- Active
- Date posted
- 2026-10-12
- Open until
- 2027-01-10
- Employment type
- Full-time
- Source-listed languages
- English
- Language requirement
- Required
- Work arrangement
- On-site
- Physical workplaces
- Ljubljana, Slovenia
- Applicant eligibility
- Applicant geography not specified
- Arrangement scope 1
- Ljubljana, Slovenia: On-site
Location and working arrangements
Applicant eligibility: Applicant geography not specified
Physical workplaces: Ljubljana, Slovenia
- Ljubljana, Slovenia: On-site
Overview
The engineering work automates the creation of sports data and video-derived content. Tasks can involve tracking players and balls, recognising events, estimating positions and interpreting visual scenes. The role researches and compares methods, then integrates useful results into products with practical accuracy and real-time constraints. Collaboration with a distributed specialist team supports knowledge sharing, but this particular position has an onsite working model. Clean implementation, reusable components and reviewable code are part of moving from an experiment to a dependable service that reduces manual operator work.
Requirements
- At least three years of professional computer-vision and machine-learning experience.
- At least two years with deep-learning frameworks.
- Expert Python and sound software-engineering fundamentals.
- Experience with modern development methods, Git and code review.
- Strong English communication.
- Independent, structured problem-solving and teamwork.
Responsibilities
- Research and implement computer-vision and machine-learning methods.
- Compare accuracy and optimise for real-time operation.
- Integrate algorithms into production products.
- Write documented, reusable code and participate in reviews.
Conditions
- Full-time onsite employment in Ljubljana, Slovenia.
- Five office days per week.
Tech stack
- Python
- PyTorch
- TensorFlow
- Git
