Software Engineer
US$200,000 – US$248,000 / yr base salary
Posted 26 Mar 2026
Advertised as “Software Engineer (Full Stack) - SME”
BranchFactor Summary
The original posting with the fluff stripped out
- Expected experience
- 14+ yrs
- Management level
- People management
| Base salary | US$200,000 – US$248,000 / yr |
|---|
What Impact You'll Have:
Join a mission-focused team where your work directly supports critical national security objectives. We are seeking a Subject Matter Expert (SME) Full Stack Developer to lead the design, development, and delivery of scalable, mission-driven applications within an ML/Ops environment. This role combines deep technical expertise with advanced system-level thinking and close collaboration across engineering, data science, and customer stakeholder teams.
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.