Machine Learning Engineering Lead, Ziva

This role is remote and open everywhere : Sydney, Vancouver, Toronto, Montreal or Europe.

We are looking for a visionary and experienced leader to direct the Ziva Machine Learning team. Ziva character tools bring cutting-edge techniques and workflows to professional 3D character artists, empowering them to create realistic and dynamic animated performances. Ziva’s ML team develops solutions to all aspects of photorealistic performance capture and character animation, integrating a variety of domains including computer vision; 3D geometry, rendering, animation, video, audio, and natural language processing. Our tools are used in world-famous film and TV productions, and we collaborate with some of the best technical artists in the world to make stunning animated content. Advancements in ML/AI are happening at a breathtaking pace, and we need a seasoned ML Lead to guide and support our team in adopting the latest best practices and technologies that deliver real value and keep Ziva and DNEG on the cutting edge of animation technology.

 

Key Responsibilities / Job Duties

As ML Engineering Lead, you will drive the successful development and deployment of machine learning solutions into world-class character animation projects. You will report to the Director of Ziva Character Tools, and collaborate directly with other team leads within Ziva and across DNEG. In partnership with key stakeholders and users, you will help set the vision, direction, priorities, and roadmap for the Ziva Machine Learning team, and be accountable for successfully delivering the agreed-upon milestones. You will guide and coordinate the work of the Ziva ML team, ensuring high velocity and quality of the solutions being created. You will identify opportunities for high-impact contributions, for example from published research or user feedback, and steer those ideas all the way from experimental prototypes to robust features of stable production software. In collaboration with your team, you will continuously improve the state-of-the-art in the quality and scalability of character animation and performance capture solutions.

 

Job Requirements / Must Haves

• Expertise in Machine Learning engineering and all aspects of model development and deployment
• Trained and deployed 3D computer vision and generative AI models into production
• Hands-on understanding of cutting-edge ML/AI techniques and their applications, e.g. diffusion models, gaussian splatting
• Proficiency in 3D computer vision, with strong fundamentals in 2D and 3D concepts and techniques
• Experience leading and mentoring a team of ML Researchers, ML Engineers, and Data Engineers
• Track record of being a force multiplier for ML development and team velocity
• Proven ability to read, implement, and refine novel techniques from research literature
• Strategic thinking and ability to drive change

 

Additional Skills / Nice to Have

• Expertise in face/body tracking and/or performance capture technologies
• Built, fine-tuned and deployed generative models for 2D and/or 3D graphics
• Familiarity with tools for 2D and 3D content creation, e.g. Maya, Houdini, Nuke
• Previous successful collaborations with professional animators and animation technical artists, in Games and/or Film.

About You 

• Critical eye for details
• Proactive
• Team oriented
• Adaptable
• Calm under pressure
• Strong communication abilities

 

Please note that this is a unionized position and will be covered by a collective agreement between DNEG and IATSE, in the coming months. As a unionized employee, you will be required to join the union and will benefit from the conditions set out in the collective agreement. Union dues will be required once the collective agreement is in place. The base salary range for this full-time position is $160,000 to $185,000. DNEG salary ranges are determined by function, department, level and location. An individual's pay within a given range is determined by their transferrable or job-related skills and work experience. Salary ranges are modified from time to time based on external market data collected through our third-party surveys.