Talanto Deutschlandweit vor 2 Tagen

Senior Data Scientist (Machine Learning Engineer)

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Das ist der Job

What you will do Develop and optimize ML models for brick-shape recognition using 3D point cloud data.

Darum lohnt es sich

Collaborate with cross-functional teams to prototype, validate, and scale machine learning solutions. Culture & Benefits Flexible work-life balance with the ability to split time between home and office.

Senior Data Scientist (Machine Learning): Designing and optimizing ML models for 3D point cloud and image recognition with an accent on MLOps best practices and scalable architecture. Focus on building intelligent systems for physical shape recognition and integrating them into production-ready pipelines.

Location: Must be based in the Czech Republic (Remote/Hybrid) Company Ciklum is a custom product engineering company with over 4,000 specialists, delivering end-to-end solutions for multinational organizations and startups. Build and improve computer vision models for image-based recognition tasks.

Ensure ML development and deployment align with internal MLOps standards and CI/CD pipelines. Participate in code reviews, architecture discussions, and continuous improvement activities. Requirements Location: Must be based in the Czech Republic. Hands-on MLOps experience including model lifecycle management and MLFlow.

Solid experience with computer vision techniques and workflows. Practical experience working with 3D point cloud data. Strong software development skills with Python. Experience with DevOps tooling and infrastructure. Nice to have Experience with Databricks and GPU-accelerated workloads. Knowledge of Docker and Kubernetes.

Familiarity with Amazon S3 or similar cloud storage platforms. Background in software architecture patterns or hardware-integrated ML environments. Access to Udemy, internal meetups, workshops, and language courses. Comprehensive medical insurance and mental health support. Financial and legal consultation services.

Opportunities for professional growth through diverse large-scale global projects. #J-18808-Ljbffr

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