Software Engineer, AI Engineer (Applied​/Software), Machine Learning​/ ML Engineer

Description

Assured Information Security (AIS) is looking for talented Software Engineers to join our Cyber AI team. AIS’s Cyber AI team develops and delivers cutting‑edge AI/ML, Cyber, and Intelligence capabilities. We’re looking to hire engineers at different experience levels. These onsite positions are located at our headquarters in Rome, NY.

Role Focus:
Engineering and research support across software development, AI/ML integration, sensor data handling, and edge‑focused systems.

Core Responsibilities May Include:

• Support development of modular, open system components and standardized interfaces.
• Assist with containerization workflows (Docker, Kubernetes, lightweight edge containers).
• Implement, test, and troubleshoot components of resilient server‑to‑edge or distributed networking frameworks.
• Contribute to integration of sensor data pipelines (visual, radar, RF, acoustic, etc.).
• Help optimize AI/ML models for constrained computing environments (e.g., embedded GPUs/NPUs).
• Participate in demonstrations, documentation, and regular code deliveries per program milestones.

Required Skills

• Familiarity with Python, C++, Linux development environments.
• Basic understanding of ML frameworks (PyTorch, Tensor Flow).
• Exposure to sensor processing or embedded systems is a plus.
• Ability to work with APIs, data serialization formats (JSON, protobuf), and real‑time data streams.

Education / Experience

• Bachelor's degree in Computer Science, Computer Engineering, Math, Physics or related field.
• 0–2 years’ experience OR equivalent combination of education and experience.

Role Focus:
Research and develop features or subsystems related to sensing, AI reasoning, distributed compute, and edge system optimization.

Core Responsibilities May Include:

• Lead implementation of elements of the program's foundational system architecture (compute, networking, trusted processing, APIs).
• Design and implement multimodal sensor fusion pipelines for real‑time or near‑real‑time inference.
• Extend and integrate AI/ML models, including LLM‑based or agentic reasoning components, into the Intelligence Engine.
• Build and tune inference pipelines for embedded or resource‑constrained devices (GPU/CPU/NPU optimization, quantization, batching, caching).
• Contribute to design improvements for system robustness in degraded or intermittent network conditions.
• Deliver subsystem documentation, contribute to technical reviews, and support integration/field testing events.
• Provide mentorship to E1 engineers and help enforce engineering standards.

Required Skills

• Strong proficiency in software engineering and systems integration.
• Experience with ML model deployment or optimization.
• Understanding of distributed systems, high‑performance edge computing, or embedded platforms.
• Familiarity with retrieval pipelines, vector databases, or multimodal AI processing is a plus.

Education / Experience

• Bachelor's degree in Computer Science, Computer Engineering, Math, Physics or related field.
• 2+ years’ experience OR equivalent combination of education and experience.

Role Focus:
Lead technical development of major subsystems, drive architectural decisions, integrate advanced AI reasoning and multimodal sensing, and ensure reliable operation in real‑world environments.

Core Responsibilities May Include:

• Define and lead architecture for major components of an end‑to‑end framework.
• Oversee integration of multimodal sensing, real‑time reasoning, structured decision logic, and data‑driven analytics into a unified operational pipeline.
• Lead design and implementation of agentic/LLM‑based reasoning frameworks (planner/executor, structured memory, context management).
• Architect highly efficient edge‑execution profiles, including computer pipeline tuning, model restructuring, and throughput‑latency optimization.
• Direct laboratory, hardware‑in‑the‑loop, and field‑relevant integration/testing cycles.
• Collaborate with program stakeholders, contribute to system architecture deliverables, and ensure compliance with engineering milestones.
• Provide technical leadership, mentorship, and…