Machine Learning Engineer

Software Engineer (III) Location: Kirkland, WA (Hybrid / Onsite Preferred) Role Overview This role sits at the intersection of Data Analytics and Software Engineering. The primary mission is to work with large-scale geospatial and location-based datasets, analyze results to identify data quality issues, and enhance existing Java-based algorithms and data pipelines through debugging and targeted improvements. The ideal engineer enjoys hands-on analysis, problem-solving, and improving system accuracy by connecting insights from data back to production code. Key Requirements & Skills Category Requirement Experience Minimum 2+ years (open to more experienced engineers). Java Intermediate level. Must be able to write clean, production-quality code and ramp up quickly on an existing codebase. SQL Advanced proficiency (approximately 4+ years). Strong querying skills for data extraction and analysis are essential. Data Analytics High proficiency. Ability to analyze evaluation results and identify patterns, errors, and opportunities for improvement. Critical Thinking Very high. This is the most important skill. The role requires troubleshooting why data is failing and determining how to fix it in both data and code. Technical Expectations • Work Split: Approximately 50% data analysis and 50% Java development. • Coding Style: Low volume but high impact. The focus is on debugging, maintaining, and incrementally improving existing pipelines rather than building new systems from scratch. • No Greenfield Development: No new system architecture, infrastructure changes, or visualization design work. All core systems are already in place. • ML Background: Candidates with machine learning experience are welcome, provided they have strong Java skills and heavy hands-on data analytics experience. • Domain Knowledge:\_logout: Domain experience with maps, geospatial data, or location-based systems is a strong plus but not required.