Geopandas Python Jobs (NOW HIRING)

The Full Stack Developer will perform rapid application design, ETL, data analysis, and interpretation while developing rules and methodologies for data collection and analysis. You will architect, develop, and maintain a Python-based data warehouse processing system that serves as the backend for a user-facing application, while also leading development of modern GUI applications using REST APIs and contemporary web frameworks. You will work closely with data scientists, computer vision engineers, ETL engineers, and intelligence analysts to integrate machine learning capabilities into production systems, enabling scalable model deployment, monitoring, and continuous improvement.

This role emphasizes ownership, technical leadership, and delivery of production-ready solutions that operate reliably in dynamic, real-world environments. What You'll Be Owning: • Lead and participate in the architectural design of complex features early in the development lifecycle. • Translate customer requirements and roadmap priorities into technical solutions, tasks, timelines, and resource plans.

• Develop, integrate, and maintain full stack applications supporting ML/Ops pipelines and data-driven systems. • Design and implement scalable APIs and services to support machine learning model deployment and inference. • Develop and maintain data pipelines, ETL processes, and data storage solutions for large-scale datasets.

• Collaborate with data scientists and ML engineers to operationalize models within production environments. • Optimize application and system performance for scalability, reliability, and efficiency, including edge and distributed environments when applicable. • Conduct peer reviews and establish coding standards to improve overall code quality and maintainability.

• Guide development testing, exploratory testing, automated testing, and validation strategies. • Own code in production environments, respond to incidents, and lead root cause analysis and continuous improvement efforts. • Ensure security, compliance, and governance are maintained throughout the development lifecycle.

• Perform technical planning, system integration, verification and validation, and risk assessments across system components. • Mentor and develop junior and mid-level engineers, fostering technical growth and high-performing teams. • Drive adoption of modern ML/Ops practices, tools, and automation frameworks across the team.

What You Must Have: • Active TS/SCI clearance with the ability to obtain a CI poly • Bachelor's degree in Computer Science, Engineering, or a related technical field. • 14+ years of professional experience in full stack software development. • Expert-level proficiency in Python and object-oriented design patterns.

• Extensive experience developing backend systems, APIs, and data processing pipelines. • Strong experience with modern web development frameworks, including React.js, Node.js, and/or Electron. • Deep understanding of data modeling techniques and experience working with large-scale and time series datasets.

• Experience with relational and non-relational databases such as PostgreSQL, MongoDB, and BigQuery. • Experience building and maintaining RESTful APIs and microservices architectures. • Experience supporting machine learning workflows, including model integration, deployment, and monitoring.

• Familiarity with ML/Ops tools and utilities such as MLflow, DVC, and/or Optuna. • Strong experience with Python libraries such as NumPy and Pandas. • Experience with Python web frameworks such as Flask, FastAPI, Pydantic, Gunicorn, and Uvicorn.

• Experience with containerization and DevOps practices, including Docker and CI/CD pipelines. • Experience with web servers such as Apache and Nginx. • Experience working within Agile development environments and using associated tools.

What Would be Nice to Have: • Experience supporting government or defense-related programs. • Experience integrating computer vision or machine learning capabilities into operational systems. • Knowledge of real-time data processing, streaming architectures, or distributed systems.

• Experience with cloud-based ML/Ops environments and infrastructure (AWS, Azure, or Google Cloud Platform). • Experience with parallelization and multiprocessing frameworks such as Dask. • Knowledge of geospatial data processing tools and libraries including GeoPandas, Shapely, Rasterio, QGIS, and ArcPy.

• Experience with machine learning frameworks such as Scikit-learn, TensorFlow, or PyTorch. • Experience with remote procedure call technologies such as gRPC and JSON-RPC. #LI-CM1