Machine Learning Engineer, NeRF / Gaussian Splatting

Machine Learning Engineer, NeRF / Gaussian Splatting

Bay Area, CA

Engineering /

Full-Time /

Remote

Apply for this job

Our mission at DigitalFish is to help our customers derive transformative value across their organizations by building next-generation technologies that define the future of digital-media creation and consumption for millions of users.

We have partnered with leading digital media companies, and are at the center of their efforts to build a new generation of platforms and experiences. Current and past customers include Apple, Google, Meta, Disney, DreamWorks, Activision, Technicolor, ESPN, LEGO, NASA and many others.

THE ROLE

The ideal candidate will have a strong background in computer vision, machine learning, and deep learning, as well as experience working with neural radiance fields. As a member of our team, your work will be critical in advancing our technology and staying at the forefront of innovation in the field of computer vision and machine learning for AR/VR.

WHAT YOU'LL DO

• Develop and implement state-of-the-art neural radiance field models for various applications such as novel view synthesis, 3D reconstruction, and relighting
• Collaborate with cross-functional teams to integrate neural radiance field models into existing systems and products
• Design and implement efficient and scalable algorithms for training and deploying neural radiance field models
• Evaluate and analyze the performance of neural radiance field models and identify areas for improvement
• Write clean, maintainable, and well-documented code
• Collaborate within the team and cross teams, working with researchers and software
• engineers
• Prioritize usability, maintainability, scalability, ease of debugging and clear documentation

WHO YOU ARE

• Bachelor's or Master's degree in Computer Science, Electrical Engineering, or related field
• Strong background in computer vision, machine learning, and deep learning
• Experience with neural radiance fields and related techniques such as volume rendering, gaussian splatting, and differentiable rendering
• Proficiency in Python and experience with deep learning frameworks such as PyTorch
• Strong troubleshooting and debugging skills
• Clear and effective written and verbal communication skills.
• Demonstrated successful collaboration with teams from varying domains and backgrounds
• Familiar with basic computer vision concepts and knowledge, including depth estimation, multiple view geometry, and related fields*
• Experience with large-scale dataset processing and management*
• Knowledge of C++ and experience with real-time graphics programming*
• Experience with building and maintaining ML infrastructure*

COMPENSATION & BENEFITS

• The annual compensation includes equity (per qualifications)
• The annual salary range for this position is $125,000 to $150,000 plus equity (per qualifications)
• The base pay offered will take into account internal parity, job-related knowledge, skills, and experience among other factors
• Health Insurance - Medical, Dental, Vision and Life Insurance
• Discounts on movie tickets, theme parks, hotels, Broadway and Vegas shows, shopping partners & more
• Flexible working environment and more!

$125,000 - $150,000 a year

ADDITIONAL INFO

DigitalFish is an equal opportunities employer ensuring that all applicants are treated equally and fairly throughout our recruitment process. We are determined to ensure that no applicant experiences discrimination on the basis of sex, race, ethnicity, religion or belief, disability, age, gender identity, ancestry, sexual orientation, veteran status, marriage and civil partnership, pregnancy and maternity, or any other basis prohibited by applicable law.

DigitalFish may share your personal information and resume with trusted partners only as necessary to help facilitate your employment journey.

DigitalFish is not able to sponsor immigration petitions for this role at this time.

All applicants must have the right to work in the United States.

We look forward to hearing from you!

Apply for this job