Senior Applied Computer Vision Engineer - Data Driven Development

As an Applied Computer Vision Engineer focused on Data Driven Development, you will be a critical part of our feature team, responsible for building and scaling the infrastructure that powers our advanced perception systems. You will architect and implement the robust data pipelines and cloud-native workflows that enable the development, training, and evaluation of next-generation computer vision models. This role is ideal for an engineer passionate about data systems, MLOps, and enabling large-scale machine learning.

Responsibilities

Design, implement, and maintain scalable data pipelines and cloud-based workflows for computer vision applications; Architect efficient database schemas, queries, and end-to-end data pipelines to support large-scale data operations; Develop and scale Azure-based data pipelines to manage high-throughput workloads, including the processing, versioning, and management of millions of images; Build, automate, and manage robust training and evaluation pipelines using frameworks like PyTorch and TensorFlow; Integrate ML pipelines seamlessly with cloud storage and compute services, particularly Azure Blob Storage and Azure ML Compute; Analyze existing models and data workflows to identify and implement performance improvements and optimizations; Implement best practices for data quality, monitoring, and infrastructure-as-code; Document system architecture, data flows, and operational procedures

Requirements

Bachelor’s degree in Computer Science, Electrical Engineering, or a related field; 2-4 years of professional experience in data engineering, MLOps, or a similar role supporting machine learning workflows; Proven experience designing and implementing scalable data pipelines and cloud-based workflows; Strong proficiency with cloud platforms, specifically Azure (AzureML, Azure Blob Storage, Azure ML Compute); Hands-on experience with data processing and orchestration tools such as Databricks or Ray; Proficiency in containerization technologies, especially Docker; Experience building or maintaining training/evaluation pipelines using PyTorch or TensorFlow; Experience with or exploration of data visualization and analysis tools (e.g., Voxel); Proficiency in Python and a strong understanding of object-oriented programming; Familiarity with essential software development tools like Git and working in a Linux environment; BE CS

Nice to have

Master’s degree in a relevant field; Prior experience in the ADAS, autonomous driving, or robotics domains; Experience with other cloud platforms (e.g., AWS, GCP); Knowledge of model optimization and deployment (e.g., TensorRT, ONNX); Hands-on experience with C++ is beneficial