Overview
Skills
Job Details
AI/ML Software Engineer for Signal Processing Applications
Minimum Qualifications
We are looking for an engineer with a solid foundation in artificial intelligence and machine learning applications to help us solve challenging problems related to signal processing. The right candidate will have a high degree of drive and dedication, and the ability to learn quickly, work well within a team, and hit the ground running.
Required:
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Bachelor's degree or higher in Computer Science, Electrical Engineering, Computer Engineering, Mathematics, or a related field
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Minimum 3 years of hands-on experience in AI or ML in a professional environment (3 5 years preferred)
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Strong knowledge of:
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Machine learning model development and deployment
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Modern ML libraries such as TensorFlow, PyTorch, scikit-learn, etc.
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Solid programming background with experience using statistical and signal analysis libraries
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Experience with neural network architectures, including deep learning models
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Understanding of transformer architectures and attention mechanisms
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Strong understanding of MLOps, deployment pipelines, processing workflows, and testing/validation
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Active TS/SCI clearance required
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U.S. Citizenship required
Nice to Have (Not Required):
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Understanding of digital signal processing (DSP) fundamentals
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Experience with RFML (Radio Frequency Machine Learning)
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Experience with Large Language Models (LLMs) including fine-tuning and prompt engineering
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Knowledge of AI applications for autonomous decision-making and analysis
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Additional consideration for experience with multimodal, agentic systems using:
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Retrieval-Augmented Generation (RAG)
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Chain of Thought (CoT) reasoning
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Multi-Agent Reinforcement Learning (MARL)
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Experience with:
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Reinforcement learning, human feedback, and related learning methods
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Creating and deploying containerized AI models using Docker and Kubernetes
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Cloud AI platforms (e.g., AWS Bedrock, Azure OpenAI, Google Vertex AI)
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Model monitoring, A/B testing, and performance optimization
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Real-time inference systems and low-latency model serving
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Adversarial ML and AI security/robustness techniques
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Graph Neural Networks (GNNs) for network analysis
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End-to-end design, deployment, and support of AI/ML models in real-world applications
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Job Description
Job Duties:
You will be responsible for designing, developing, and implementing AI/ML solutions for a wide range of decision-making and SIGINT processing needs. This includes working with time-series data and developing models for:
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Event characterization
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Pattern recognition
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Anomaly detection
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Decision making
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Automated analysis of SIGINT sensor systems
You will work with team leads to integrate AI/ML capabilities into enterprise architectures, ensuring performant processing with consideration for accuracy, security, and maintainability.
Your work will also include:
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Enabling autonomous decision-making systems that operate with minimal human intervention
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Creating adaptive processing systems for dynamic environments
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Discovering features and inferring system states from data streams
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Delivering tailored models that provide intelligent insights at scale in support of critical Intelligence Community and Department of Defense missions