Machine Learning Engineer - Computer Vision
Workplace: Göteborg, Sverige
Expires: December 13, 2025
We are looking for an experienced Machine Learning Engineer with a strong background in computer vision and generative AI to develop systems that generate realistic, diverse, and highly controllable synthetic image data using state-of-the-art tools such as Stable Diffusion, LoRA, and ControlNet. The role involves improving AI systems applied in real-world domains like self-driving cars and defense robotics.
Main requirements:
  • MSc or PhD in Computer Vision, Machine Learning, or related field
  • 3+ years of hands-on experience with deep learning frameworks (e.g., PyTorch, TensorFlow)
  • Experience with generative AI models, especially diffusion-based models
  • Familiarity with tools like LoRA, ControlNet, ComfyUI, or custom workflows around Stable Diffusion
  • Strong understanding of synthetic data generation for training perception systems
  • Track record of deploying ML systems in automotive, robotics, defense, or manufacturing domains
Responsibilities:
  • Develop and fine-tune generative AI pipelines (Stable Diffusion, ControlNet, LoRA) for synthetic image generation
  • Design and implement ML workflows to generate structured, photorealistic datasets
  • Collaborate with 3D artists and simulation engineers to align ML models with physical and sensor environments
  • Work closely with automotive, robotics, and aerospace customers to deliver tailored datasets
  • Optimize generation systems for scalability, quality, and speed with tools like ComfyUI or custom pipelines
Required hard skills:
  • Deep learning frameworks (PyTorch, TensorFlow)
  • Generative AI models (diffusion-based)
  • Tools such as LoRA, ControlNet, ComfyUI
  • Synthetic data generation and perception system training
  • ML system deployment in relevant domains
Recommended hard skills:
  • 3D simulation pipelines
  • Sensor modeling (depth, LiDAR, segmentation)
  • Custom diffusion model training
  • Synthetic-to-real domain adaptation techniques
Soft skills:
  • Problem-solving intellect
  • Team player
  • Positive can-do attitude
  • Enjoy reading research papers
Frameworks:
  • PyTorch
  • TensorFlow
Natural languages:
  • English (Proficient)
Cultural skills:
  • Collaborative work with artists and engineers
  • Engagement with customers in high-tech domains
  • Startup environment experience
  • Working with enterprise R&D teams