Top Tech Jobs & Startup Jobs

Summer intern develops real-time machine learning systems and GPU-accelerated digital signal processing algorithms for streaming RF data. Responsibilities include filtering, spectral analysis, waveform generation, data pipeline development, ML model training, outcome analysis, system integration, and deployment using DevOps and MLOps tools. The intern collaborates with engineers on communications, radar, and other defense and intelligence applications.

Leads a portfolio of advanced technology programs spanning computer vision, AI/ML, signal processing, software, and mission systems. Oversees execution, budgets, staffing, risk, customer commitments, and financial performance while developing approximately 20–30 technical employees and leaders. Partners with program, product, finance, HR, and talent teams to improve delivery, recruit staff, plan workforce needs, and build high-performing organizations supporting defense and intelligence customers.

Develop and optimize ML and computer vision models for hyperspectral and multi-modal sensor data, build detection/tracking and data fusion algorithms, translate research into deployable software, and support solutions across cloud and low SWaP environments for geospatial intelligence applications.

Design and implement DSP solutions for intelligence and defense applications, researching advanced DSP and machine learning algorithms for radar, electronic warfare, SIGINT, and RF geolocation. Develop models and transition them into real-time, field-ready software. Responsibilities include prototyping, full-system design, deployment across on-premises and cloud platforms, and operational integration.

Deploy and optimize computer vision, signal processing, and machine learning algorithms on GPU-enabled embedded systems. Improve real-time performance on constrained low-SWaP platforms, profile CPU/GPU bottlenecks, select algorithms based on hardware constraints, containerize deployments, and produce Linux-based production software. Collaborate with machine learning and software engineers to transition models into operational environments.

Design and implement backend and systems-level software for defense and intelligence applications. Integrate machine learning and signal-processing algorithms into real-time systems, transition models into field-ready applications, collaborate with domain experts, and build extensible software solutions for complex customer requirements.

Design and implement complex backend and systems-level software for defense and intelligence applications. Integrate machine learning and signal-processing algorithms, transition models into real-time field systems, architect and integrate software systems, prototype algorithms, and translate customer requirements into extensible solutions.

Designs and leads scalable Python software systems supporting U.S. Government missions. Responsibilities include architecture, distributed systems, cloud-native Kubernetes deployments, CI/CD automation, observability, reliability, troubleshooting, testing, and operational excellence. The role provides technical leadership and mentorship while collaborating with engineers and mission stakeholders. Candidates must hold an active TS/SCI clearance and bring extensive production software engineering experience, cloud expertise, and strong system integration skills.

Design and implement production-grade Python services and internal tools supporting verification, validation, testing, and evaluation workflows for DoD and intelligence missions. Build scalable, maintainable, and testable systems; establish engineering, testing, and observability best practices; contribute to mission-critical architecture; support containerized deployments and CI/CD automation; and mentor teammates.

Develop and deploy DevSecOps capabilities for defense-focused prototype systems. Responsibilities include containerizing Python applications, deploying workloads to Kubernetes, building CI pipelines and developer tooling, delivering infrastructure as code, troubleshooting Linux networking and storage, supporting cloud-native applications, and ensuring compliance with NIST, CMMC, and CIS controls.