ML Researcher

About the role

You will implement POCs in Python and C++ to validate machine learning concepts on embedded hardware under real time constraints. You will conduct research in imaging and video processing pipelines tailored for AR and VR applications where latency and reliability are critical. You will document technical learnings and define clear pathways to transition prototypes into production grade systems. You will research and implement model optimization techniques that enable deployment on edge devices without sacrificing accuracy. You will stay current with the latest developments in computer vision and machine learning literature to ensure the team remains at the forefront of the field. You will prototype novel algorithms and validate their performance through rigorous experimentation against state of the art baselines. You will design and implement end to end machine learning pipelines using PyTorch and TensorFlow Lite for diverse operational environments. You will optimize models to meet strict real time performance requirements on mobile and embedded platforms. You will implement MLOps best practices for model versioning, monitoring, and continuous integration to streamline deployment. You will create scalable data preprocessing and augmentation pipelines that ensure robustness across diverse real world conditions.

Key facts

What you'll do

• Implement POCs in Python/C++ to validate ML ideas on embedded hardware
• Conduct research in imaging and video processing pipelines for AR/VR applications
• Document learnings and define clear pathways from prototype to production
• Research and implement model optimization techniques for edge deployment
• Stay current with latest developments in computer vision and machine learning literature
• Prototype novel algorithms and validate performance through experimentation
• Design and implement end-to-end machine learning pipelines using PyTorch and TensorFlow Lite
• Optimize models for real-time performance on mobile and embedded platforms
• Implement MLOps best practices for model versioning, monitoring, and continuous integration
• Create scalable data preprocessing and augmentation pipelines
• Partner with cross functional teams to align research initiatives with product roadmaps and operational constraints
• Translate ambiguous problem statements into concrete experimental plans and measurable success criteria
• Evaluate deployed models in production to identify regressions and drive iterative improvements
• Mentor junior engineers and researchers by sharing insights through code reviews and technical discussions

Requirements

• BS with a minimum of 5+ years of academic or industry experience in machine learning research or applied ML engineering with shipped or published work (or MS with 2+ yrs of the above)
• Proficiency in Python with experience in ML frameworks (PyTorch, TensorFlow)
• Experience with ML pipeline development, model deployment, and production monitoring
• Knowledge of quantization, pruning, and edge deployment techniques
• Strong understanding of software engineering practices including version control, testing, and debugging
• Ability to work independently and collaboratively in a fast paced, mission driven environment
• Willingness to adhere to strict compliance requirements regarding work authorization and documentation
• Commitment to maintaining high standards of accuracy, reliability, and safety in developed systems

Nice to have

• PhD in Computer Vision, Machine Learning, or related field
• Publications in top-tier conferences (CVPR, ICCV, ECCV, NeurIPS, ICML)
• Experience with AR/VR or mobile computer vision applications
• Knowledge of CUDA programming and GPU optimization
• Experience with cloud platforms (AWS, GCP, Azure) for ML workloads
• Familiarity with containerization (Docker, Kubernetes) and CI/CD pipelines
• Experience with distributed training and large-scale data processing
• Understanding of sensor fusion, pose estimation, and SLAM concepts
• Exposure to computational photography and camera calibration workflows
• Familiarity with IMU and multi sensor integration techniques

Practical notes

Work Authorization Requirement: Due to the nature of our business and compliance with federal regulations, all candidates must be a "U.S. Person". Upon hire, you will be required to provide documentation verifying your status as a U.S. Citizen, a lawful permanent resident, or a protected individual under 8 U.S.C. 1324b(a)(3).

Compensation may vary within the posted range based on relevant experience, skills, education, and other job-related factors. In addition to base salary, this role may be eligible for equity and other forms of compensation.