Applied Scientist (Computer Vision)

Job Summary

Join a distributed team developing high-performance motion detection features for Cloud and Edge environments. Choose an Edge focus, working with advanced computer vision algorithms and sensor-based detection for efficient real-time on-device performance, or a Cloud focus, building scalable cloud-based motion detection solutions and optimizing Edge–Cloud collaboration.

You will conduct day-to-day research by defining hypotheses, collecting experimental data, training and validating ML models, validating results, and writing a paper on the findings.

Responsibilities and Duties

• Develop innovative machine learning algorithms.
• Implement advanced methods and technologies in model development.
• Analyze large datasets to identify correlations and patterns.
• Visualize research results for clearer interpretation.
• Tune hyperparameters and optimize algorithms to improve model performance and accuracy.
• Consult and collaborate with colleagues from other departments.
• Report project progress and achievements to management.
• Explore and evaluate new machine learning technologies; implement cutting-edge ideas and techniques in production processes.
• Continuously develop technical skills and mentor junior colleagues.

Qualifications and Skills

• 4+ years of machine learning experience in the computer vision domain.
• Practical experience with at least one of: classification, detection, or segmentation.
• Python3, NumPy, scikit-learn, pandas, and SciPy.
• PyTorch.
• Experience deploying machine learning models to production.
• Strong understanding of machine learning and deep learning concepts.
• Good written and spoken English.

Nice to Have

• Practical experience with GANs and VAEs.
• Probabilistic programming and Bayesian frameworks.
• Model optimization, including pruning, quantization, and knowledge distillation.
• Basic understanding of web and client-server architecture.
• asyncio, aiohttp, and other asynchronous back-end libraries.
• Basic understanding of Big Data, including the difference between MapReduce and in-memory processing.
• Algorithms and data structures.
• SQL and NoSQL.
• Docker, Kubernetes, Kubeflow, C++, and Bash.

Benefits

• Equal-opportunity, transparent, value-based culture with an individual approach to team members.
• Competitive salary packages with annual performance-based reviews.
• Performance Bonus for individual achievements and Loyalty Bonus for dedication.
• Employment under a Contract of Employment (UoP) aligned with Polish Labour Law.
• Paid vacation, public holidays, and medical leave in line with statutory regulations.
• Growth opportunities through internal knowledge hubs, corporate courses, and free English classes.
• Private medical insurance supplementing NFZ coverage.