Lead Machine Learning Engineer

Focused on the future of filmmaking, Wonder Dynamics is an LA-based start-up founded by Actor/Producer, Tye Sheridan who’s starred in films like Ready Player One, X-Men: Apocalypse, Mud, and VFX Supervisor/Filmmaker Nikola Todorovic. Their mission is to revolutionize the production and post-production process by leveraging state-of-the-art AI. They are striving to democratize the use of visual effects which will pave the way for the next generation of filmmakers. That mission attracted some of the most influential individuals in the film and tech industry that are now involved in their teams. Wonder Dynamics is backed by Epic Games, Samsung, Horizons Ventures (a Hong Kong VC firm with early investments in Skype, Siri, Facebook and more) and Founders Fund, a leading Silicon Valley VC that funded some giants like Space X, Facebook, Spotify, DeepMind, etc.)

Their Advisory Board consists of leaders in Hollywood and Silicon Valley:

  • Joshua Baer, founder/CEO of Capital Factory
  • Terry Douglas, Producer and financier of Film and TV. Founder of Rhea Films,
  • Angjoo Kanazawa, assistant professor at UC Berkeley and Google research scientist;
  • Joe Russo Director, screenwriter, and Producer (directed Avengers: Infinity War and Avengers: Endgame)
  • Robert Schwab – Private equity investor, President, and CEO of R&L Properties
  • Steven Spielberg – Film director, producer, and screenwriter
  • Antonio Torralba – Professor and Head of AI and Decision making, EECS,
  • Massachusetts Institute of Technology (MIT)
  • Gregory Trattner – President, Film Finances Inc.

About the Role

We are seeking an experienced Lead Machine Learning Engineer to join our team. In this role, you will bring your passion for AI, innovative technologies, and the film industry to design and implement cutting-edge machine learning algorithms in the fields of visual effects, motion capturing, rendering, and other areas of film production. The ideal candidate will bring exceptional leadership and communication skills to lead a team of engineers and collaborate closely with other departments.

What we are looking for

  • At least 4 years of professional experience in the field of Machine Learning and/or
  • Computer Vision, or an advanced degree (MSc).
  • Experience in applied Deep Learning (DL) and Computer Vision (CV) concepts including but not limited to: CNNs, RNNs, Autoencoders, Transfer Learning.
  • Hands-on experience (academic and/or industrial) in 3D Pose Estimation and
  • Motion reconstruction from images and videos
  • Proficiency in general-purpose programming languages: Python, and C++.
  • Experience with ML frameworks such as: PyTorch, Tensorflow, etc.
  • The ideal candidate would be very well acquainted with Computer Graphics techniques, Neural Rendering, and Numerical Optimization
  • (Optional) Knowledge of 3D packages such as Blender, Maya, or any game engine technology
  • BSc in Computer Science, Mathematics, Electrical Engineering, or a related technical field
  • Ability to speak and write in English fluently

Why you should consider joining us

At the intersection of film and technology, this job will offer a very unique experience, and you will be exposed to a diverse set of fields spanning from film production and visual effects to AI, machine learning, and computer vision. Because we are operating in state-of-the-art territory, there will always be something new to learn on the horizon. We highly value our team and the support of our co-workers and strive to create the best environment to work in. This is a mid- or senior-level engineering role and we offer a competitive salary, valuable stock options, and comprehensive benefits that allow individual flexibility for all employees to choose what makes the most sense for their personal situation. Wonder Dynamics is committed to a culture of flexibility, diversity, and fun for all of our employees. We are working on some of the most challenging technical problems and we know the solutions will come from all of us working together in an inclusive, transparent, and open manner.

Flexible working hours

  • Remote, in-office & hybrid opportunities are available.

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