Artificial Intelligence & Machine Learning Systems Engineer

Were 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 this leadership role youll 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.

Major Duties & Responsibilities:

• 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.

Why This Role is Different:

• You will own the entire stack from algorithm research to bare-metal deployment on platforms that fly float or roll into harms 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

Required Qualifications:

• Bachelors in Computer Science Machine Learning Artificial Intelligence Data Science or related field
• 7 plus 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

Preferred Qualifications:

• Masters degree in Computer Science Machine Learning Artificial Intelligence Data Science or related field
• 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

Preferred Developer/Admin Skills:

• 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: Material UI
• System administration: Linux Windows VMWARE
• GenAI: Pytorch Tensorflow

The annual base salary range for this position in California (excluding most major metropolitan areas) New York (excluding most major metropolitan areas) Colorado Connecticut and Hawaii is $170500 $213200. For Washington and most major metropolitan areas in New York and California (including San Diego and San Jose) the annual base salary range is $196160 $245200. Please note that this salary information serves as a general guideline. Honeywell considers various factors when extending an offer including but not limited to the scope and responsibilities of the position the candidates work experience education and training key skills as well as market and business considerations.

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: January 6 2026.

BENEFITS OF WORKING FOR HONEYWELL

In addition to a performance-driven salary cutting-edge work and developing solutions side-by-side with dedicated experts in their fields Honeywell employees are eligible for a comprehensive benefits package. This package includes employer-subsidized Medical Dental Vision and Life Insurance; Short-Term and Long-Term Disability; 401(k) match Flexible Spending Accounts Health Savings Accounts EAP and Educational Assistance; Parental Leave Paid Time Off (for vacation personal business sick time and parental leave) Paid Holidays and this role may be eligible for a 9/80 schedule.

U.S. PERSON REQUIREMENTS

Must be a US Citizen due to contractual requirements

ABOUT HONEYWELL

Honeywell International Inc. (Nasdaq: HON) invents and commercializes technologies that address some of the worlds most critical demands around energy safety security air travel productivity and global urbanization. We are a leading software-industrial company dedicated to introducing state-of-the-art technology solutions to improve efficiency productivity sustainability and safety in high-growth businesses in broad-based attractive industrial end markets. Our products and solutions enable a safer more comfortable and more productive world enhancing the quality of life of people around the globe.

THE BUSINESS UNIT

Honeywell Aerospace Technologies (AT) products and services are found on virtually every commercial defense and space aircraft in the world. We build aircraft engines cockpit and cabin electronics wireless connectivity systems mechanical components and more and connect many of them via our high-speed Wi-Fi offerings. Our solutions create healthier air travel more fuel-efficient and better-maintained aircraft more direct and on-time flight arrivals safer skies and airports and more comfortable flights along with several innovations and services that reflect exciting and emerging new transportation methods such as autonomous and supersonic flights. Revenues in 2023 for Honeywell Aerospace Technology were $14B and there are approximately 21000 employees globally.