计算机视觉与AI工程师（男女皆可）

your tasks

• Develop and deploy vision-based perception algorithms for autonomous inspection robots using deep learning and machine vision techniques, including CNN- and ViT-based architectures.

• Design and implement supervised, self-supervised, and unsupervised learning methods for multi-modal data (RGB, LiDAR, thermal, etc.).

• Build and optimize models for:
• Object detection and tracking (2D & 3D)

• Anomaly detection

• LiDAR-based semantic segmentation and 3D point cloud understanding

• Optimize models for on-device inference (quantization, pruning, distillation) and deploy them on edge hardware (NVIDIA Jetson Xavier/Orin/Thor, etc.).

• Integrate perception pipelines into robotic systems via ROS1/ROS2 and collaborate closely with software and robotics teams.

• Support MLOps workflows, ensuring reproducible training, evaluation, and CI/CD for AI models.

• Support and maintain cloud-based AI pipelines on AWS (SageMaker, Bedrock, Lambda, S3) for scalable training, inference, and model lifecycle management.

• Contribute to research on multi-modal and 3D representations (Gaussian Splatting, NeRF, OpenCLIP-based embeddings).

• Participate in continuous improvement of our AI infrastructure for mission planning, semantic mapping, and robot autonomy.

your profile

• Degree in Computer Science, Robotics, or a related technical field.

• 2+ years of professional experience in computer vision, deep learning, or robot perception.

• Strong understanding of Vision Transformers (ViTs), Convolutional Neural Networks (CNNs), and DETR-based models for object detection.

• Hands on experience with Frameworks including PyTorch, OpenCV, MMDetection, and/or Detectron2.

• Applied experience in Optimization & Deployment with TensorRT, ONNX, Docker, and/or NVIDIA DeepStream.

• Direct experience with Data Annotation using CVAT, and/or Label Studio, and/or 3D Point Labeler.

• Practical experience in Versioning & MLOps using GitLab CI/CD, MLflow, n8n, AWS SageMaker, and/or Bedrock.

• Strong programming skills in Python, C++, Bash.

• Strong analytical, problem-solving, and growth mindset.

• Excellent collaboration between cross-functional AI and robotics teams.

• Passion for innovation, autonomy, and pushing the boundaries of perception systems.

• Ability to work independently and manage multiple priorities in a fast-paced environment.

• Fluent in English.

helpful additional qualifications

• Experience with LLMs, VLMs, VLAs and multi-modal embeddings.

• Familiarity with semantic scene graphs-based 3D Gaussian splatting.

• Exposure to cloud-based data services or AI workflow orchestration.

• Contributions to open-source projects in AI/robotics or publications in the field.

Originally posted on Himalayas