AI Data Scientist II

Location: Remote, United States

Salary: $98,000–$134,000 base salary annually, bonus eligible

Company

Builds geospatial intelligence and AI systems that transform high-resolution aerial imagery into actionable insights for environmental monitoring, disaster response, urban planning, construction, government, and infrastructure management.

What you will do

• Evaluate machine learning and agentic AI systems using metrics for task success, accuracy, robustness, reliability, and common failure patterns.
• Apply and maintain evaluation methods for computer vision models covering detection, segmentation, and classification.
• Develop quantitative metrics, test harnesses, reusable scripts, notebooks, and curated datasets for production-representative scenarios.
• Perform model comparisons, stress tests, edge-case testing, error analysis, and root-cause investigations.
• Analyze accuracy, processing time, resource use, and regressions, then communicate actionable recommendations to engineering, product, and research partners.
• Document code, data, configurations, results, limitations, and evaluation methods for repeatable technical work.

Requirements

• Bachelor’s degree or equivalent practical experience in data science, machine learning, statistics, computer science, or a related field.
• Two to four years of relevant experience in data science, machine learning, model evaluation, or a related technical field.
• Hands-on experience evaluating machine learning models with quantitative metrics and clearly documented results.
• Working knowledge of computer vision evaluation for segmentation, detection, or classification models.
• Exposure to LLM-based, multimodal, or agentic systems and multi-step evaluation workflows.
• Proficiency in Python and machine learning or data science libraries such as NumPy, Pandas, or scikit-learn, plus Git and at least one cloud environment such as AWS or GCP.

Nice to have

• Experience evaluating image classification, document classification, LLM, or RAG applications.
• Experience creating reusable evaluation scripts, notebooks, dashboards, or quality assurance tools.
• Experience in a collaborative software or machine learning development lifecycle.

Culture & Benefits

• Full-time remote work within the United States.
• Collaborative environment focused on continuous improvement and cross-functional communication.
• Paid time off, sick leave, and parental leave.
• Medical, dental, vision, life, pet, and employee assistance program benefits.
• 401(k) plan and health savings account.