Remote AI Infra Engineer

Summary

Join our team and help us transform the grocery industry by designing, developing, and maintaining our data platform for deep learning and computer vision applications.

Requirements

• Bachelor’s or Master’s degree in Computer Science, Engineering, or a related field
• 5+ years of experience in data engineering, full-stack and/or infrastructure development
• Proven experience with building and maintaining large-scale data pipelines (batching or streaming) for computer vision and/or machine learning applications
• Familiarity with observability and monitoring tools (e.g. Datadog) and best practices
• Familiarity with frameworks for large-scale data processing (e.g., Kafka, Spark, Airflow, Ray), storage (e.g., S3, Delta Lake), indexing and search (e.g. Elasticsearch)
• Experience with cloud platforms (e.g., AWS, GCP) and containerization technologies (e.g., Docker, Kubernetes)
• Strong problem-solving skills to work in a fast-paced, dynamic environment
• Excellent communication skills to work collaboratively in a cross-functional team

Responsibilities

• Design, build, and maintain scalable and efficient data pipelines for collecting, processing, and storing large volumes of structured and unstructured data, specifically image and video streams and relevant metadata
• Develop and integrate tools for data labeling and annotation, ensuring high-quality training datasets for deep learning and computer vision models
• Collaborate with data scientists and machine learning engineers to build and optimize the infrastructure required for training and evaluating deep learning models at scale
• Build and maintain CI/CD pipelines to seamlessly deploy machine learning models into production environments

Preferred Qualifications

• Experience building and/or integrating computer vision data collection, labeling and management systems
• Experience in edge inference and optimization on Nvidia chipsets
• Experience with deep learning frameworks (e.g., TensorFlow, PyTorch) and model management platforms (e.g., Kubeflow, MLflow, TensorBoard)
• Knowledge of computer vision and machine learning algorithms and models

Benefits

• Market-competitive compensation
• Flexible work arrangement (Flex First)
• New hire equity grant
• Annual refresh grants