B2B

AI/ML

We are seeking a highly skilled and hands-on Machine Learning Engineer to join the Algorithm team.

You will be the primary owner and executor of the new customer onboarding process for both our computer vision and multimodal systems.

The focus is on executing the current partially-automated pipelines while simultaneously engineering solutions to reduce manual intervention, leading to full automation and reduced time-to-market.

Responsibilities

Customer Onboarding: Execution and Automation (Core Focus)
- End-to-End Execution: Execute the complete new customer onboarding workflow for both projects, from initial data readiness to final deployment. This includes:
  - Data Preparation: Managing the 'man in the loop' steps to prepare and validate new customer-specific data (logos, entities) for training
  - Model Training & Retraining: Executing and monitoring existing training pipelines. for the YOLO-based Logo Detection system, and initiating training for the Smart Linkage components
  - Evaluation: Running and analyzing standard evaluation procedures and metrics to ensure models meet customer-specific performance benchmarks before deployment
  - Configuration & Deployment: Setting specific configuration files for features like Graphics Brands Types locations and entity mapping, and managing the final model deployment
  - Pipeline Optimization: Systematically identify bottlenecks and manual steps within the current onboarding process and engineer solutions to reduce "man in the loop" time, moving toward fully autonomous MLOps pipelines

Internal Tooling & Infrastructure Improvement:Design and implement scalable internal tools and scripts to simplify and automate repetitive tasks across the evaluation and data preparation stagesOptimize model serving and inference performance to meet low-latency customer requirements
- Design and implement scalable internal tools and scripts to simplify and automate repetitive tasks across the evaluation and data preparation stages
- Optimize model serving and inference performance to meet low-latency customer requirements
Data Flow Collaboration and Support (Supporting Duty)
- Collaboration with Tagging Team: Work alongside the professional data taggers and the algorithm developer responsible for their output to ensure a smooth, timely flow of high-quality, labeled data
- Assist in prioritizing labeling tasks and performing data quality checks to ensure data is ready for the training pipelines
Evaluation tools to reduce manual labor and to get proper quality metrics

Requirements

Education: Degree in Computer Science, Electrical Engineering, or a related field (focus on AI/ML/CV)
Python Proficiency: Expert-level Python skills with a commitment to writing clean, modular, and maintainable code
ML Frameworks: Hands-on experience with PyTorch, TensorFlow, or scikit-learn
Production Mindset: Solid understanding of the full ML lifecycle (preprocessing, training, evaluation, and deployment)
Experimentation: Experience running, analyzing, and documenting ML experiments to identify optimal approaches
Excellent team player, dependable, and results-oriented

What we offer

Competitive salary range
Medical insurance
Paid vacation and sick leaves
MultiSport card
Top equipment kit, co-workings
Hybrid set of works (Office location: Warsaw)
Collaborative and innovative work environment
Career growth and development opportunities
A chance to work with giants of the sports industry

About the project

Our partner leads the industry in generating dynamic sports videos for every digital destination. Their cutting-edge AI and Machine Learning technologies analyse live sports broadcasts from over 250 leagues and broadcast partners, including iconic names like the NBA, NHL, ESPN, FIBA and Bundesliga, to create personalized, short-form videos in real-time.

The solution empowers media rights owners to unlock new revenue streams and deliver a tailored fan experience across every digital platform. Join the high-profile Engineering team and discover the forefront of sports contents innovation.