Artificial Intelligence & Machine Learning Systems Engineer-Cognitive Electronic Warfare (EW)
CAES
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Benefits offered by this job
Job summary
Qualifications
- 7+ years of professional experience shipping production AI/ML systems, ideally in defense.
- Prior work on DoD cognitive EW programs.
- Hands-on experience building and securing CI/CD pipelines.
Responsibilities
- Design, implement, and harden ML algorithms for RF signal classification.
- Lead the systems integration of AI/ML techniques into mission-critical platforms.
- Own the MLOps and DevSecOps pipeline for classified EW programs.
Skills
Education
Tools
Job description
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Delivering mission‑critical, electronic solutions that protect lives. Use your creativity and critical thinking to take our products from concept to customer.
At CAES by Honeywell, we engineer solutions for the world’s most critical missions. We serve customers in the defense and aerospace markets. Seeking a career that offers challenging, diverse projects and opportunities? Looking for a position with a company that offers long‑term professional advancement? Searching for a place that values a diverse, team‑based environment? One that values YOU. Consider CAES by Honeywell.
The most important thing we build is TRUST
#CustomerFocus #Values #Leader #TogetherWePioneer
We’re seeking a highly skilled Artificial Intelligence & Machine Learning Systems Engineer to architect, design, and develop advanced AI/ML systems that power our next generation of products. In this leadership role, you’ll contribute to the technical roadmap, mentor engineering teams, and collaborate with cross‑functional teams to deliver intelligent, scalable, and production‑ready AI and machine learning technologies. You will be responsible for researching, creating, adapting and evaluating AI/ML techniques to solve complex customer problems with real‑time solutions to support our defense customers.
Specifically, we are building next‑generation cognitive electronic warfare systems that operate autonomously at the tactical edge in contested, low‑Swap (Size, Weight, and Power), denied, and disconnected environments. This is not a prompt‑engineering or GenAI role. We are looking for hardcore AI/ML systems engineers who treat machine learning as a component of a larger, mission‑critical, real‑time embedded system.
- Design, implement, and harden on‑line and continual‑learning ML algorithms for RF signal classification, adaptive jamming, cognitive radar, and electronic attack/support decision engines.
- Port, optimize, and deploy ML inference algorithms to edge processors.
- Build and maintain low‑latency, deterministic inference pipelines that integrate tightly with real‑time RF front‑ends and digital signal processing chains.
- Lead the systems integration of AI/ML techniques into mission‑critical embedded platforms running real‑time operating systems.
- Design and deliver warfighter‑focused engineering visualizations and tactical displays (real‑time spectrum awareness, threat emitter tracks, cognitive EW decision overlays, confidence heatmaps) using modern web stack frameworks that run natively on embedded tactical processors and dismounted soldier systems.
- Own the MLOps and DevSecOps pipeline for classified EW programs: secure CI/CD, model versioning, containerized build/test/deploy, SBOM generation, and compliance with DoD zero‑trust and CNCF security standards.
- Architect and deploy Kubernetes‑based edge orchestration clusters (e.g. k3s) that operate in fully air‑gapped tactical environments with strict latency and availability requirements.
- Perform end‑to‑end performance profiling (memory bandwidth, cache coherency, DMA, GPU/TPU/NPU utilization).
- Review code, guide architecture decisions, and mentor the AI/ML engineering team.
- Collaborate with product and engineering teams to identify AI/ML‑driven opportunities.
- Bachelor’s or Master’s degree in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or related field
- 7+ years of professional experience shipping production AI/ML systems, ideally in defense, aerospace, or autonomous systems
- Prior work on DoD cognitive EW programs
- Deep expertise in high‑performance and real‑time applications (not just scripting wrappers)
- Real‑time and embedded application programming (no Python‑only backgrounds)
- Proven track record of deploying AI/ML solutions to cloud and edge/constrained devices
- Strong systems engineering background: you understand clocks, interrupts, DMA, cache hierarchies, memory‑mapped I/O, and real‑time scheduling
- Hands‑on experience building and securing CI/CD pipelines for classified or regulated environments
- Expertise with Docker, container hardening, and Kubernetes in disconnected/edge configurations (k3s, microk8s, Rancher Harvester).
- Familiarity with RF/ML intersections: signal detection & classification, modulation recognition, emitter geolocation, fingerprinting, adaptive waveform design, or reinforcement learning for EW
- Proficiency with ML algorithms (including NLP, Computer Vision, time‑series), libraries including foundational understanding and expertise in statistics probability theory and linear algebra
- Strong understanding of machine learning fundamentals: supervised/unsupervised learning, deep learning, model evaluation, optimization, feature engineering, etc
- Experience with data engineering workflows and building robust training datasets
- Experience as the technical lead for establishing and accrediting classified AI/ML information systems under the DoD Risk Management Framework (RMF):
- Author and maintain System Security Plans (SSP), Security CONOPS, and AI/ML‑specific risk annexes
- Build and harden multi‑enclave classified development, integration, and operational environments (RHEL 8/9, SELinux enforcing, DISA STIGs, Assured Compliance Assessment Solution (ACAS))
- Lead the creation of AI/ML‑specific artifacts for eMASS packages, including model cards, data provenance, adversarial robustness testing, and continuous monitoring plans
- Obtain and maintain Authority to Operate (ATO) for classified cognitive EW systems containing advanced GPU/NPU‑accelerated AI infrastructure
- Perform Linux systems administration at the classified level: kernel tuning for real‑time determinism, custom security hardening, cross‑domain solution integration, auditd/ELK stack management, and FIPS 140‑3 compliant cryptography
- Deep Linux systems administration and hardening experience in classified environments (RHEL/CentOS, STIG compliance, SELinux policy authoring)
- Hands‑on experience authoring RMF packages and obtaining ATOs for systems containing machine learning components for the U.S. Government (Army, Navy, Air Force, or IC customer)
- Expertise with Docker, container hardening (CIS, OSCAP), and Kubernetes in disconnected tactical environments
- Experience or exposure with implementing Government reference architectures
- Experience with neuromorphic or spiking neural network hardware (Intel Loihi, BrainChip Akida)
- Experience with distributed training, GPU acceleration, and high‑performance ML compute
- Strong background in foundation algorithms, transformers, or multimodal AI
- Knowledge of automated model monitoring, drift detection, and lifecycle management
- Experience integrating ML models into consumer or enterprise products
- Language: C/C++, GoLang, Powershell, Carbon, Java, Python, Javascript, CUDA, OpenCL, VHDL
- Orchestration/deployment: Kubernetes/k3s, containerd, OpenVino, OSGi
- Distributed: Hazelcast, REST architecture, websockets, NEO4J
- DevSecOPS: Cmake, Maven, Ansible, Google JIB, Gradle, Jenkins, Git, Helm
- Visualization: Node.js, React.js, Material UI
- System administration: Linux, Windows, VMWARE
- GenAI: Pytorch, Tensorflow
- Strong leadership, communication, and technical mentorship abilities
- Thrives in fast‑paced environments with a passion for continuous learning
- Ability to translate complex AI/ML concepts for non‑technical partners
- Competitive salary + performance bonuses
- Equity opportunities
- Full benefits package (health, dental, vision, 401k)
- Flexible working environment
- Opportunity to shape the direction of AI/ML initiatives from the ground up
- You will own the entire stack from algorithm research to bare‑metal deployment on platforms that fly, float, or roll into harm’s way
- No Python notebooks in production—everything is compiled, containerized, signed, and deployed with cryptographic integrity
- Real impact: your code will out‑think and out‑maneuver adversary emitters in real conflicts. If you live for the intersection of cutting‑edge machine learning and extreme systems engineering under the harshest constraints, we want to talk to you
Salary Range: $196,160.00 - $245,000.00 annually
Employees may be eligible for a discretionary bonus in addition to base pay. Applicable pay within the posted range may vary based on factors including, but not limited to, geographical location, job function of the position, education, and experience of the successful candidate.
CAES provides a variety of benefits including health insurance coverage, life and disability insurance, 401K, paid holidays and vacation.
The application period for the job is estimated to be 40 days from the job posting date; however, this may be shortened or extended depending on business needs and the availability of qualified candidates. Job Posting Date: December 10, 2025.
- Comprehensive PTO, Paid Holiday and Paid Family Leave Programs.
- Student Loan Repayment Program & Tuition Reimbursement
- 9/80 Alternate Work Week Schedule
- Tailored Management/Leadership Training
- Innovative Medical Programs, Including Family Forming
CAES by Honeywell pioneers advanced electronics that underpin many of the world’s most critical missions. We design, engineer, test, and manufacture advanced electronic solutions for the U.S. aerospace and defense industry. From inception and development engineering, to full‑rate production and sustainment, we work closely with customers as partners throughout the program lifecycle.
At CAES by Honeywell we welcome differences and celebrate new ideas. We believe the diversity of our people inspires our creativity and drives our innovation. Everyone is welcome here, regardless of race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, protected veteran status, or genetic information.
We are committed to working with and providing reasonable accommodations to individuals with disabilities. If you need a reasonable accommodation due to a disability for any part of the employment process, please email CAEScareers@caes.com.
Not Applicable
Full‑time
Defense and Space Manufacturing
Referrals increase your chances of interviewing at CAES by 2x
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