Cloud MLOps Engineer supporting Data Science and Engineering teams by automating CI/CD pipelines and managing multi - cloud infrastructure for ML production.
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
Lead development of Agentic AI capabilities and LLM applications for multiple mission management applications. Mentor teams to implement ML algorithms addressing customer challenges.
Staff AI/ML Engineer at CACI responsible for developing AI/ML algorithms and analyzing datasets. Join a high - performing team supporting national safety missions.
AI/ML Engineer at CACI developing machine learning algorithms for multiple applications. Collaborating with a research team to implement cutting - edge AI/ML solutions for customer missions.
Senior Computer Vision AI/ML Engineer leading a team in AI/ML algorithm implementation for remote sensing solutions. Responsibilities include training models and analyzing datasets with a focus on defense and commercial applications.
MLOps Engineer working on ML processes and robust workflows at Kensho. Collaborating with engineers to enhance tooling, services, and frameworks for machine learning.
Intern working on avionics hardware and software for Blue Origin. Gaining hands - on experience while contributing to space development projects.
Machine Learning Engineer engaged in recommendation and search, NLP, and image processing. Contributing to a major online dating app, Pairs, in Japan.
Senior Scientist II leading innovative AI and machine learning projects in oncology at Tempus. Collaborating with teams to advance predictive modeling and drug R&D initiatives.
Technical leader architecting and deploying advanced Gen AI and ML solutions for Walmart Connect. Driving innovation in ad targeting, personalization, and campaign analytics.