Senior Software Engineer

Senior Software Engineer – Scientific Data Systems

Remote (US) or Hybrid | Full-Time | Defense & Intelligence Sector

A company working at the intersection of satellites, RF detection, and data analytics is hiring a Senior Software Engineer to join their algorithms group. This team owns the pipeline that pushes massive volumes of radio frequency data through DSP and geolocation algorithms, then turns that into a product for government and commercial customers.

This isn’t a research role. It’s a production software role where code needs to be clean, memory‑efficient, tested, and reliable. The algorithms already exist. Your job is to build the plumbing that connects them together, handles large volumes of incoming data, and delivers the output in a repeatable, scalable way.

This sits in the DSP org, working directly with signal processing, ML, and data engineers. They’re looking for someone who’s built real production systems in Python and C++, has a strong grasp of computational complexity, and is comfortable navigating large‑scale scientific or time‑series data.

• Building and maintaining performant code in Python and C++
• Creating reusable components that support DSP and geolocation algorithms
• Handling large datasets and deploying software into a containerized, cloud‑based environment
• Supporting CI/CD pipelines and writing automated tests
• Collaborating across teams to keep software stable, scalable, and reliable

• 5+ years of experience writing production software in Python and C++
• Familiarity with cloud environments (AWS preferred) and containerized deployments (Docker, Kubernetes)
• Comfort working in Linux-based environments
• Experience with standard Python libraries like Num Py, pandas, and Sci Py
• Solid understanding of software performance, memory, and data complexity
• Experience with Git-based CI/CD (Git Lab preferred)

• Background in signal processing or having worked around RF datasets
• Experience with orchestration tools like Airflow or Dagster
• Familiarity with pybind
  11, or building C++/Python integrations
• Exposure to data quality systems and validation tools
• Experience deploying data or ML-based products to customers

You’ve built and shipped software that handles complex data be you worked at a company delivering data feeds or running data platforms as a product. You understand how to move large datasets around, and why code structure and computational cost matters when things get big. You’re not afraid to own a chunk of code and keep it running.

Adam Slade