Were looking for a seasoned Machine Learning Engineer who is passionate about building intelligent and immersive AR this role youll architect and deliver advanced ML and computer vision solutions that bring real-world and digital environments together. Youll work closely with cross-functional teams-product managers designers and engineering teams-to transform innovative ideas into scalable real-time AR applications.
If you enjoy solving complex technical challenges pushing the boundaries of AR/VR/XR and leading strategic ML initiatives this role is for you.
Key ResponsibilitiesLead end-to-end development of machine learning models for AR-from research and prototyping to model training optimization and production deployment.
Build and optimize computer vision and deep learning models for object detection tracking segmentation spatial mapping and real-time scene understanding.
Develop real-time inference pipelines for mobile and edge devices (iOS Android AR glasses and XR hardware).
Work with technologies such as 3D reconstruction SLAM scene mapping gesture recognition and sensor fusion.
Integrate ML models into AR platforms including ARCore ARKit Unity Unreal Engine or custom XR frameworks.
Continuously improve performance latency accuracy and overall user experience for AR workloads.
Provide mentorship and technical leadership while driving ML best practices and architecture decisions.
Collaborate on roadmap planning and contribute to overall technology strategy.
12 years of experience in Machine Learning Deep Learning and Computer Vision.
Strong expertise in building ML models for AR/VR/XR or other real-time interactive 3D applications.
Solid hands-on experience with CNNs RNNs Transformers 3D CV models Diffusion models and Generative AI.
Advanced programming skills in Python and experience with frameworks such as TensorFlow PyTorch OpenCV ONNX.
Experience in model optimization (quantization pruning) and edge deployment.
Practical exposure to SLAM pose estimation optical flow point clouds LiDAR and depth sensors.
Experience integrating ML models into Unity/Unreal is a strong advantage.
Knowledge of GPU acceleration and CUDA-based optimization.
Experience deploying ML systems using MLOps tooling (MLflow Kubeflow Airflow Docker Kubernetes).
Excellent communication team collaboration and leadership skills.
Masters or PhD in Computer Science AI/ML Robotics or related field.
Experience working with ARCore ARKit Vision Pro Meta Quest HoloLens or similar platforms.
Cloud experience with AWS GCP or Azure and familiarity with real-time streaming data pipelines.
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