Sr Software Engineer

### Who you are
- Master’s degree in Computer Science or related field plus 5 years of related experience or Bachelor’s degree in Computer Science or related field plus 7 years of relevant experience
- Design and development of backend and frontend applications, build and maintain internal data labeling tools using Python, React/NodeJS, PyQT, and Django frameworks (5 yrs)
- Development of image processing pipelines using Python scientific, numpy, and CUDA, adjusting images across data channels and content or objects (3 yrs)
- Use Kubernetes to develop, deploy, and harden data science and labelling applications, support hybrid training workloads via Kubeflow and multi-cluster orchestration tools (3 yrs)
- Develop massive parallel data analytics and visualization pipelines using AWS, Apache Spark & Databricks for CVML and Fleet Analytics workloads (3 yrs)
- Finetuning and training visual models using Pytorch framework, design meta-orchestration frameworks to coordinate labeling, training, and monitoring pipelines (5 yrs)
- Orchestrate ML, Data processing, and self-healing workloads using MLFlow, Kubeflow, and Snakemake orchestration framework (3 yrs)
- Low-level model optimization and scaling using C++, ONNX (3 yrs)
- Design and implement real-time image processing pipelines using OpenCV, scikit-image, and CUDA for embedded and cloud-based applications (3 yrs)
- Own and manage the lifecycle of ML experiments across tools, including MLflow, AIM, TensorBoard, and W&B (3 yrs)
- 10% domestic or international travel required for whole team meetings and to work on on-premises solutions. 100% remote working allowed; can live anywhere in the US; periodic visits to the office required

### What the job involves
- Develop and maintain real-time image processing pipelines and integrate hardware sensors for computer vision applications
- Design and automate data labeling and preprocessing
- Manage and scale machine learning experimentation and training infrastructure
- Design and implement hardware-in-the-loop technologies to develop and validate autonomous systems
- Implement and oversee orchestration and meta-orchestration systems to enable seamless CVML pipeline execution across hybrid cloud environments