Senior Machine Learning Engineer

Stop Seeing. Start Feeling. At Leia, we're bringing the 3D richness of our world into the digital domain, revolutionizing how we work, play and connect. We are a collective of visionaries, innovators, and pioneers on a mission to make 3D available to everyone, anywhere, on any device. Join us and be part of a movement where your contributions don't just make a mark but redefine the digital horizon. What You’ll Do As a Senior Machine Learning Engineer within the Computer Vision group, you will be working on face detection, generative AI image synthesis, computational photography and computer vision. In this role you will be responsible to be a driving force of prototyping, developing, and integrating cutting-edge imaging and computational photography technologies. Some of the core vision tasks you might work on are: - Real time Face Detection and Pose Estimation - Real time Head Tracking and Prediction - Depth/Disparity estimation from a Single Image or a Stereo Image - Image View Synthesis from a Single/Stereo Image + Disparity Map - Generative inpainting of de-occluded regions - Text-to-Image generation of stereo images While a strong focus will be on Deep Learning model training towards high quality output, you may also be involved in dataset generation, data cleaning, augmentation, and productization/optimization/deployment for running on various platforms.You will work as part of a professional motivated multi-disciplinary team working to deliver state of the art experiences for 3D Displays including Leia’s award winning Lume Pad 2 and future generation devices. What You’ll Have - BS or MS in Computer Science or Electrical Engineering or equivalent. - 7+ years of software development imaging and ML experience. - 2+ years of experience building deep learning architectures for commercial products - Excellent knowledge of Python and working knowledge of C/C++. - Proven track record developing and deploying ML models in production for image segmentation, disparity estimation or image synthesis. - Proficiency with CNN architectures such as ResNet, VGG, UNet, Stacked Hourglass, MobileNet, pix2pix, and CycleGAN - Experience with distributed training (PyTorch, Tensorflow, etc.) - Experience with optimizing model training performance - Experience to scale model training to large number of GPUs/CPUs or other accelerators - Experience with commercial software development processes: good software hygiene regarding code documentation, unit testing, bug tracking, and version control. - Highly motivated, team player with strong technical collaboration skills and desire to learn quickly and develop new skills. Nice to Haves - Experience with Android and Java is a big plus - Experience with Face detection and/or Head Tracking and prediction - Experience with GPU/DSP model optimization - Experience with ML model deployment on devices - Experience with Lightfield technology - Experience with stereo vision, photogrammetry, computational photography, or related tasks - Experience with sensor fusion - Publications relevant to Computer Vision and/or Deep Learning What We Offer In order to assemble top talent to help realize this mission Leia offers our employees: - Competitive Compensation Package - Medical, Dental, and Vision Plan - Retirement Savings Plan 401(k) - Catered lunch and dinner daily (Dependent on Location) - Stocked kitchen with healthy (and unhealthy) snacks and beverages - Onsite workout facility (Dependent on Location) This is a position based in Menlo Park, CA/Ukraine/Remote. The US base salary range for this full-time position is $220,000 - $240,000. The range displayed on the job posting reflects the minimum and maximum target for new hire salaries. Within the range, individual pay is determined by work location and additional factors, including job-related skills, experience, and relevant education or training. Please note that the compensation details listed in US role postings reflect the base salary only, and do not include bonus, equity, or benefits. Leia Inc. is an Equal Opportunity Employer. Candidates are evaluated without regard to age, race, color, religion, sex, disability, national origin, sexual orientation, veteran status, or any other characteristic protected by federal or state law.