Computer Vision Research Intern, Parallel Domain

• Level: PhD students (must have prior relevant publications)
• You are actively pursuing a PhD in computer science or a related field at a world renowned university
• You are well-versed with developing machine learning models for computer vision tasks
• You have published peer-reviewed research in at least one of these areas: 3D Computer Vision and Scene Reconstruction, Generative Modeling (GANs, Diffusion models, 3D Gaussian Splatting), Image and Scene Synthesis (Inpainting, Style Transfer), Semantic Segmentation or Automated Scene Understanding, Domain Adaptation or Sim-to-Real techniques
• You have prior experience with Pytorch, Tensorflow, or Keras
• You're eager to learn You are a team-player and understand the importance of clear communication
• You thrive in ambiguous environments
• You are not afraid to approach new challenges
• You are fluent in english

Desirable

• We’re excited to bring on exceptional PhD Research Interns for summer and extended research opportunities
• This is your chance to dive deep into advanced Computer Vision and Machine Learning research, collaborate daily with experienced professionals, and make immediate real-world impact
• Duration: Ideally 12-16 weeks (can extend up to 6 months)
• You’ll be part of the ML team tasked with establishing best practises on creating and using synthetic data for perception
• You will work directly with our team to perform cutting-edge research in one or more of these key areas: 3D computer vision, generative models for image/video/scene generation, style transfer, image inpainting, neural rendering, and related areas
• You’ll develop, experiment, and integrate advanced CV algorithms into our platform
• You’ll summarize your findings to help guide our team as well as our customers
• You’ll sync with your team on a daily basis to discuss progress, ideas and problems
• You’ll work with veterans from the gaming, movie and automotive industry

• Flexibility to work from our office in the San Francisco Bay Area or your home office
• Competitive compensation
• Employer-paid supplemental medical, mental health, dental, and vision benefits
• 401(k)
• Paid vacation and sick time, winter shutdown, and 11 stat holidays each year
• Paid parental leave
• New hire equipment + accessories budget to optimize your setup
• $1,500 annual learning and development allowance

Total funding: $43.9m

Autonomous vehicles are fast making the leap from science fiction to reality. However, there are huge safety implications that need to be addressed. Parallel Domain has developed software for training autonomous vehicles in a virtual setting, reducing the risks associated with real-world testing and giving vehicle manufacturers the ability to identify problems and put them right, before the vehicle ever hits the road.