Machine Learning Engineer (m/f/d)

• *This position is based in Bulgaria with hybrid or remote working options. Applicants must hold a valid work/residence permit for the respective location.**

Chaos is a leading global software company that provides world-class visualization and design solutions, empowering creative minds to bring ideas to life.

For over twenty years, Chaos has developed innovative technologies serving multiple industries, including architecture and design, media and entertainment, and product e-commerce. Chaos’ solutions help architects, designers, VFX artists/animators, and other creative professionals share ideas, optimize workflows, and create immersive experiences.

Headquartered in Karlsruhe, Germany, Chaos is a global company with offices in 11 cities worldwide. In 2022, Chaos and Enscape merged, bringing together two industry-leading companies into one. Since then, Chaos has continued to grow with the additions of Cylindo, AXYZ Design, and Evolve Lab, further expanding our expertise and solutions across architecture, design, e-commerce, and AI. For more information, please visit chaos.com .

Role Overview

The Machine Learning Engineer drives the innovation, development, and deployment of intelligent solutions across Chaos’ product portfolio, landing in software such as Enscape, V-Ray, Veras, and more. The role directly influences areas like image enhancement, agentic assistance, asset generation, rendering enhancements, and intuitive 3D design interactions by bridging the gap between cutting-edge ML research and production-ready software.

Key Responsibilities

Design, develop, and optimize machine learning models in one or more solutions, including asset generation and capture, render enhancement, scene intelligence, agentic design workflows, and intuitive design interactions.

Investigate and bring techniques from a variety of AI research areas, such as diffusion, super-resolution, conditioned generation, plus neural and differentiable rendering, into artists’ hands.

Evaluate, integrate, and orchestrate off-the-shelf third-party foundation models to accelerate feature development and deployment.

Mentor other engineers and contribute to the growth of the team’s knowledge and expertise in machine learning.

Collaborate with cross-functional teams and our ML Product Manager to define the product requirements and scope of delivery of solutions to product teams.

Work closely with our MLOps Engineer to develop and maintain pipelines for distributed training, inference optimization/quantization/serving, experiment tracking, model versioning & validation, and deployment to the cloud (AWS/Azure/GCP).

Implement appropriate model evaluation tests, data curation processes, and apply dataset-rights awareness, and responsible AI/governance.

Stay updated and share knowledge on the latest developments in machine learning, generative AI, natural language processing, and 3D visualization, and implement cutting-edge techniques to enhance our solutions.

Ensure high-quality code and documentation, following best practices in software development and machine learning.