Machine Learning Data Engineer

About the Company

Outpost is building the backbone of freight by reinventing supply chain infrastructure with carrier agnostic truck terminals. As a vertically integrated real estate, operations, and technology company, Outpost acquires and operates mission-critical real estate to serve the largest logistics providers in the world.

Responsibilities

• Own tracking and reporting of CV accuracy metrics per customer and identifier type
• Investigate misclassifications and false negatives to identify patterns across yards
• Curate, label, and prioritize datasets for model retraining in partnership with ML engineers
• Build and improve continuous learning pipelines to enable weekly model shipments
• Define functional acceptance criteria for CV accuracy and track progress
• Translate accuracy findings into actionable decisions for engineering and stakeholders
• Develop labeling/preprocessing tooling and own fixes for error patterns as the pipeline matures

Requirements

• 3+ years in data quality, ML data engineering, or applied ML roles
• Experience with computer vision or object detection systems in production
• Proficiency in Python for data analysis and pipeline automation
• Strong analytical rigor for digging into large volumes of imagery/data
• Experience with dataset annotation tools like Roboflow, Labelbox, or CVAT
• Strong written English communication skills for asynchronous engagement

Preferred Qualifications

• Experience with continuous learning or active learning pipelines
• Familiarity with OCR systems and identifier recognition (plates, container numbers)
• Experience partnering with customer success teams on quality metrics
• Background in QA/test engineering for ML systems
• Specific experience with Roboflow