10/09/2026 updated
100 % available
Machine Learning Engineer | Computer Vision Specialist
split, Croatia
Only remote
BSc in Computer Science (Faculty of Electrical Engineering and Computing, Zagreb)Computer VisionDevOpsPython (Programming Language)Machine LearningOpenCVPyTorchDeep Learning
Machine Learning & Deep Learning
Extensive experience in designing, training and deploying machine learning and deep learning models, including GANs, VLMs, CNNs and neural radiance fields, using frameworks such as PyTorch and PyTorch Lightning.
Computer Vision
Strong focus on computer vision tasks including video restoration, superresolution, depth estimation, object detection, oriented bounding box detection and inventory management in retail environments.
Cloud Infrastructure & MLOps
Deployment and scaling of ML services on AWS Kubernetes clusters, including dependency management, containerization with Docker and orchestration tools such as Kubernetes and Airflow.
Python Ecosystem
Proficiency in a wide range of Python libraries including asyncio, fastAPI, xgboost, boto3, pandas, openCV, sklearn, numpy and multiprocessing.
Programming & DevOps Tools
Hands-on experience with Linux, vllm, sglang, Docker, Redis, RabbitMQ, lakeFS, kafka, bash, ffmpeg, postgresql, SQL and NoSQL databases.
Bayesian Modeling & Optimization
Implementation of planogram optimization services using hierarchical Bayes modeling and genetic algorithms.
NAS Pipeline Development
Development of complete NAS to inference to report pipelines, including network training for detection tasks such as identifying broken insulators on powerlines.
Version Control & Collaboration
Regular use of git for version control and collaborative software development workflows.
Extensive experience in designing, training and deploying machine learning and deep learning models, including GANs, VLMs, CNNs and neural radiance fields, using frameworks such as PyTorch and PyTorch Lightning.
Computer Vision
Strong focus on computer vision tasks including video restoration, superresolution, depth estimation, object detection, oriented bounding box detection and inventory management in retail environments.
Cloud Infrastructure & MLOps
Deployment and scaling of ML services on AWS Kubernetes clusters, including dependency management, containerization with Docker and orchestration tools such as Kubernetes and Airflow.
Python Ecosystem
Proficiency in a wide range of Python libraries including asyncio, fastAPI, xgboost, boto3, pandas, openCV, sklearn, numpy and multiprocessing.
Programming & DevOps Tools
Hands-on experience with Linux, vllm, sglang, Docker, Redis, RabbitMQ, lakeFS, kafka, bash, ffmpeg, postgresql, SQL and NoSQL databases.
Bayesian Modeling & Optimization
Implementation of planogram optimization services using hierarchical Bayes modeling and genetic algorithms.
NAS Pipeline Development
Development of complete NAS to inference to report pipelines, including network training for detection tasks such as identifying broken insulators on powerlines.
Version Control & Collaboration
Regular use of git for version control and collaborative software development workflows.
Experience
Professional experience5 - 10 years
Freelancer since2026
Languages
EnglishFluentCroatianNative speaker
Project history
Writing code for a user ID verification service using a combination of VLMs and oldschool CNNs. Wrote code for a planogram optimisation service using hierarchical Bayes modeling and genetic algorithms. Deployed both services and their dependencies on the company's AWS Kubernetes cluster.
Trained and deployed efficient GAN video restoration and superresolution models. Each shipped model was faster and better than the previous one.
Developed solutions for inventory management in retail environments using computer vision. Studied state of the art in depth estimation, neural radiance fields and oriented bounding box detection. Used a novel evaluation metric to significantly reduce the memory footprint of the network.