Senior Computer Vision and Machine Learning Engineer
Golden, Colorado
Applications have closed
Outrider
Autonomous yard operations have set a new standard. Yard automation transforms yard operations into an efficient, safe, and sustainable solution.The roleThe senior CV/ML engineer will join a team that is developing the next generation perception stack for the Outrider fleet. The team is working on interesting and challenging problems in pose estimation and object detection using lidar, radar, vision, and gnss/ins.
The engineer in this role will help drive development of perception capabilities by owning the full model lifecycle from dataset curation and model development to integration with the perception pipeline.
The senior CV/ML Engineer will report to the Principal Computer Vision Engineer and develop perception software capabilities through all phases of Outrider's pilot and deployment programs. This position plays an essential role in helping deliver a reliable, profitable, performant, safety-critical system -- it offers a very talented software engineer the chance to help develop a market-defining enterprise product that combines autonomous vehicle technology with a software-as-a-service (SaaS) business model.
The ideal candidate will embrace our goal to drive zero-emission, self-driving vehicle adoption, and help us realize our potential to define, build, and lead a new category of robotic automation for the enterprise.We’re searching for a senior computer vision and machine learning engineer with at least 5 years experience developing algorithms and training models for object detection, tracking, segmentation, pose estimation, and classification of obstacle types (vehicle, truck, pedestrian, etc.) using multi-modal sensor data.
Duties and responsibilities
- Develop and train models for applications such as object detection, tracking, classification, segmentation, and pose estimation
- Evaluate model performance
- Incorporate models in perception algorithms
- Integrate models into production vehicle perception systems
- Maintain training, validation, and testing sets across customer sites and weather conditions
- Be responsible for the full software engineering lifecycle: requirements, design, source code implementation, unit test, integration, and system test
- Travel and perform fieldwork, depending on initial customer locations (up to 10%)
Required qualifications
- Masters degree in computer science or relevant field with exposure to classic and modern computer vision techniques
- 3+ years of professional C++ and Python experience
- 5+ years of professional experience training, evaluating, and deploying models with a deep learning framework such as PyTorch or Tensorflow
- Experience working on a team in a Linux environment and targeting embedded deployment
- Experience with at least one of the following: stereo vision, LIDAR, radar, and thermal sensing technology
- Excellent written and verbal communication skills
- Exceptional analytical skills
- Demonstrated strong leadership and people skills
- Sterling references
Ideal qualifications
- AWS experience with S3, SQS, Lambda, DynamoDB, and EC2Experience with docker
- ROS / software for ground robotic systems
- Experience with embedded computer vision
- Prior experience designing annotation ontologies and working with data labeling vendors
- FOSS libraries/frameworks such as OpenCV, the Point Cloud Library (PCL), and similar packages
- FOSS tools supporting software engineering, such as CMake, continuous integration packages, the Google test framework and others
- PhD and relevant publications and patents
Tags: AWS Classification Computer Science Computer Vision Deep Learning Docker DynamoDB Engineering GNSS Lambda Lidar Linux Machine Learning OpenCV PhD Python PyTorch Radar TensorFlow Testing
Perks/benefits: Career development
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