Machine Learning Engineer at Tilt, developing personalisation solutions across various app surfaces. Collaborate with teams to enhance recommendation systems on a video - first shopping platform.
About the role
- Machine Learning Engineer working with Algorithm team on customer onboarding processes. Focus on execution and automation of models using computer vision and AI in sports industry.
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.
- 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.
- Internal Tooling & Infrastructure Improvement: Design and implement scalable internal tools and scripts to simplify and automate repetitive tasks across the evaluation and data preparation stages.
- Data Flow Collaboration and Support (Supporting Duty): Collaboration with Tagging Team, assist in prioritizing labeling tasks and performing data quality checks.
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
Benefits
- 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
Job title
Job type
Experience level
Salary
Not specified
Degree requirement
Tech skills
Location requirements
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