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Machine Learning Engineer (Remote - California) at Jobgether. This position is posted by Jobgether on behalf of Nearmap. We are currently looking for a Machine Learning Engineer in California (USA).. We are seeking a skilled Machine Learning Engineer to develop and maintain scalable ML systems that support advanced data analysis and AI-driven insights. In this role, you will collaborate closely with data scientists and engineers to design pipelines, tools, and production-grade solutions that turn complex datasets into actionable intelligence. You will ensure smooth transitions from prototypes to operational systems, working in a cloud-based environment that emphasizes reliability, efficiency, and experimentation. Ideal candidates are proactive, collaborative, and passionate about building robust ML infrastructure that enables innovation at scale. This role offers exposure to cutting-edge technologies and the opportunity to contribute to impactful AI applications in a fast-paced environment.. Accountabilities. . Design, develop, and maintain machine learning pipelines for data ingestion, feature processing, model training, deployment, and monitoring.. . Adapt and extend ML tools and frameworks to meet the specific needs of data science teams.. . Integrate internal and external APIs to connect datasets, models, and services efficiently.. . Ensure infrastructure and processes support fast experimentation while maintaining reliability, security, and scalability.. . Act as a technical partner to data scientists, enabling smooth execution of modeling projects and production deployment.. . Bridge the gap between research prototypes and production-grade ML systems.. . . 2+ years of experience as a Machine Learning Engineer, ML-focused Software Engineer, or equivalent, delivering production-grade ML systems.. . Bachelor’s degree in Computer Science, Mathematics, or a related technical field.. . Strong Python skills for ML pipeline development, including experience with packages such as pandas, scikit-learn, and PyTorch.. . Proficiency in software development best practices: writing clean, maintainable, and well-tested code.. . Experience with SQL and building scalable data processing workflows (e.g., Apache Spark, Airflow, dbt).. . Strong communication skills and the ability to translate technical solutions for non-engineers.. . Highly desirable: experience with cloud environments (AWS), containerization (Docker), REST API integration, MLOps frameworks, geospatial/imagery data processing, and familiarity with insurance or property/casualty domains.. . Company Location: United States.