Interested in this AI/ML Engineer role at Korry Electronics?
Apply Now →Skills & Technologies
About This Role
Help Shape the Future of AI at Korry
Are you passionate about using Artificial Intelligence, automation, and modern technologies to solve complex business challenges? Join Korry as our Enterprise AI \& Automation Engineer and lead the development of innovative AI solutions that transform how we work across the enterprise. If you're excited to build cutting\-edge applications, drive digital transformation, and make a lasting impact in a collaborative aerospace environment, we'd love to hear from you.
What You Will Do:
As our Enterprise AI \& Automation Engineer, you will lead the design, development, and implementation of Artificial Intelligence (AI), intelligent automation, and enterprise application solutions that drive Korry's digital transformation. You will partner with Engineering, Manufacturing, Operations, Finance, Quality, Supply Chain, and Customer Service to improve productivity through AI, automation, and enterprise software solutions while reducing key\-person dependency for business\-critical applications.
Primary Responsibilities:
- Enterprise AI
- + Develop Microsoft Copilot, Copilot Studio, Azure AI Services, and ChatGPT Enterprise solutions.
+ Build AI assistants, enterprise knowledge search, Document AI/OCR, and AI\-powered decision support.
+ Implement AI governance, prompt engineering standards, and responsible AI practices.
- Enterprise Automation
- + Develop Power Automate workflows and Power Apps.
+ Automate engineering, manufacturing, finance, and operational processes.
- Enterprise Applications
- + Design and maintain C\#, .NET, and ASP.NET applications.
+ Develop REST APIs and integration services.
+ Provide production support and application modernization.
- Enterprise Systems Integration
- + Integrate IFS Gov ERP, Windchill PLM, ARAS PLM, Microsoft 365, SharePoint, SQL Server, Azure, Microsoft Graph, and third\-party SaaS platforms.
- Data \& Analytics
- + Develop Power BI dashboards and executive reporting.
+ Support SQL Server, SSRS, SSIS, and enterprise reporting.
- Security \& Compliance
- + Ensure solutions align with CMMC Level 2, NIST SP 800\-171, ITAR, CUI, RBAC, DLP, secure software development, and audit logging.
- Performs special projects/tasks as assigned.
Preferred Education
- AI\-102 Azure AI Engineer
- AZ\-204 Azure Developer
- AZ\-104 Azure Administrator
- PL\-400 Power Platform Developer
- PL\-600 Power Platform Solution Architect
- AZ\-305 Azure Solutions Architect
Preferred Experience
- 7–12 years of enterprise application development.
- Experience with SQL Server, Microsoft technologies, enterprise integrations, and automation.
- Manufacturing, ERP/PLM, and AI experience preferred.
Preferred Specialized Skills and Abilities
- Programming: C\#, .NET, ASP.NET Core, SQL (T\-SQL), Python, JavaScript, TypeScript, PowerShell
- Enterprise Development: REST APIs, JSON/XML, Git, Azure DevOps, CI/CD
- Database: SQL Server, SSMS, SSIS, SSRS, Stored Procedures, Performance Tuning
- Cloud: Microsoft Azure, Microsoft 365, Entra ID, Azure Functions, Logic Apps, Service Bus
- AI: ChatGPT Enterprise, Azure OpenAI, Azure AI Services, Microsoft Copilot, Copilot Studio, Power Platform, AI Agents, Prompt Engineering, RAG, Document Intelligence
Physical Requirements:
- Frequent use of personal computers, database and digital platforms, and other office productivity machinery, such as copy machines and computer printers.
- Frequently uses hands, fingers, and arms to reach, handle, touch or feel equipment, materials, and computer.
- The person in this position needs to frequently move inside the office
- Frequent close vision and the ability to adjust focus.
Eligibility Requirements:
\*\*Must be authorized to work in the U.S.\*\*
\*\*This position requires either a US Person (as defined in applicable export regulations) or a non\-US person who is eligible to obtain required export authorization\*\*
Salary Range:
The typical hiring range for this role is:
- Level III: $124,000\-$186,000
- Level IV: $144,000–$216,000
Final offers are based on job\-related qualifications and pay equity.
Korry Electronics Competitive Benefits Package:
- 401(k) matching
- 12 paid holidays
- Minimum of three weeks paid time off plus one week paid sick time to start
- Comprehensive Medical, Dental and Vision
- Health Savings Account (HSA) with generous company contribution
- Flexible Spending Accounts (FSA)
- Tuition reimbursement
- Parental leave
- Short term and long term disability
- Life insurance
- Accidental death \& dismemberment insurance
- Long\-term care plan options
- Prescription safety shoe \& glasses benefit
- Vanpool subsidy
- Recognition awards
- Employee referral bonuses
- EAP (Employee Assistance Program)
Korry Electronics is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of age, race, color, religion, sex, sexual orientation, gender identity or expression, medical condition, national origin, marital status, disability, pregnancy or parental status, childbirth, genetic information, or military and veteran status.
### Company Description:
Eligible candidates must be authorized to work in the U.S.
This position requires access to export control information. To conform to US Export Control regulations, applicant should be eligible for any required authorizations from the US Government.
Korry Electronics is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of age, race, color, religion, sex, sexual orientation, gender identity or expression, medical condition, national origin, marital status, disability, pregnancy or parental status, childbirth, genetic information, or military and veteran status.
Thank you for your interest in Korry Electronics!
Our company culture is focused around ownership, transparency, process improvement and trust \& respect. We are looking for talented people (like you!) to lead our business to the next level while giving you the opportunity to develop your own career.
We have been at the forefront of the aviation industry since the beginning, creating the first lighted cockpit controls for the military and commercial aircraft industry. The Korry product team continues this tradition as it develops the crew station of the future, providing state\-of\-the\-art switches, cockpit controls, high\-performance displays, and night\-vision filters. We are passionate about what we do. For more information, please visit www.korry.com.
Join the Korry team and find out why this is such a great place to spend your career!
Korry Electronics is proud to be an equal opportunity workplace and is an affirmative action employer. We are committed to equal employment opportunity regardless of age, race, color, religion, sex, sexual orientation, gender identity or expression, medical condition, national origin, marital status, disability, pregnancy or parental status, childbirth, genetic information, or military and veteran status.
Salary Context
This $124K-$216K range is below the median for AI/ML Engineer roles in our dataset (median: $175K across 2162 roles with salary data).
View full AI/ML Engineer salary data →Role Details
About This Role
AI/ML Engineers build and deploy machine learning models in production. They work across the full ML lifecycle: data pipelines, model training, evaluation, and serving infrastructure. The role has evolved significantly over the past two years. Where ML Engineers once spent most of their time on model architecture, the job now tilts heavily toward inference optimization, cost management, and integrating LLM capabilities into existing systems. Companies want engineers who can ship production systems, and the experimenter-only role is fading fast.
Day-to-day, you're writing training pipelines, debugging data quality issues, setting up evaluation frameworks, and figuring out why your model performs differently in staging than it did on your dev set. The best ML engineers are obsessive about reproducibility and measurement. They instrument everything. They know that a model is only as good as the data feeding it and the infrastructure serving it.
Across the 4,317 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Korry Electronics, this role fits into their broader AI and engineering organization.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
What the Work Looks Like
A typical week might include: debugging a data pipeline that's silently dropping 3% of training examples, running A/B tests on a new model version, writing documentation for a feature flag system that lets you roll back model deployments, and reviewing a junior engineer's PR for a new evaluation metric. Meetings tend to be cross-functional since ML touches product, engineering, and data teams.
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
Skills Required
Python and PyTorch dominate the requirements. Most roles expect experience with cloud platforms (AWS, GCP, or Azure) and familiarity with ML frameworks like TensorFlow or JAX. RAG (Retrieval-Augmented Generation) has become a top-3 skill requirement as companies integrate LLMs into their products. Docker and Kubernetes show up in about a third of postings, reflecting the production focus of the role.
Beyond the core stack, employers increasingly want experience with experiment tracking tools (MLflow, Weights & Biases), feature stores, and vector databases. Fine-tuning experience is valuable but less common than you'd think from reading Twitter. Most production LLM work is RAG and prompt engineering, not fine-tuning. If you have both, you're in a strong position.
Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
Compensation Benchmarks
AI/ML Engineer roles pay a median of $214,900 based on 6,420 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $194,400. This role's midpoint ($170K) sits 21% below the category median. Disclosed range: $124K to $216K.
Across all AI roles, the market median is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. For comparison, the highest-paying categories include AI Safety ($287,500) and Research Engineer ($272,100). By seniority level: Entry: $110,000; Mid: $194,400; Senior: $227,400; Director: $274,554; VP: $241,000.
Korry Electronics AI Hiring
Korry Electronics has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Everett, WA, US. Compensation range: $216K - $216K.
Location Context
Across all AI roles, 15% (635 positions) offer remote work, while 3,657 require on-site attendance. Top AI hiring metros: New York (1,650 roles, $220,000 median); San Francisco (1,335 roles, $265,000 median); Los Angeles (708 roles, $214,112 median).
Career Path
Common paths into AI/ML Engineer roles include Data Scientist, Software Engineer, Research Engineer.
From here, career progression typically leads toward ML Architect, AI Engineering Manager, Principal ML Engineer.
The fastest path into ML engineering is through software engineering with a self-directed ML education. A CS degree helps, but production engineering skills matter more than academic credentials. Build something that works, deploy it, and measure it. That portfolio project is worth more than a Coursera certificate. For career growth, the fork comes around the senior level: go deep on technical complexity (staff/principal track) or move into managing ML teams.
What to Expect in Interviews
Expect system design questions around ML pipelines: how you'd build a training pipeline for a specific use case, handle data drift, or design A/B testing infrastructure for model deployments. Coding rounds typically involve Python, with emphasis on data manipulation (pandas, numpy) and algorithm implementation. Take-home assignments often ask you to build an end-to-end ML pipeline from raw data to deployed model.
When evaluating opportunities: Companies that are serious about AI/ML hiring tend to post specific infrastructure details in the job description: the frameworks they use, their model serving stack, their data pipeline tools. Vague postings that just say 'ML experience required' without specifics are often companies that haven't figured out what they need yet.
AI Hiring Overview
The AI job market has 4,317 open positions tracked in our dataset. By seniority: 138 entry-level, 2,071 mid-level, 1,655 senior, and 453 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (635 positions). The remaining 3,657 roles require on-site or hybrid attendance.
The market median for AI roles is $215,000. Top-quartile compensation starts at $266,300. The 90th percentile reaches $320,790. Highest-paying categories: AI Safety ($287,500 median, 34 roles); Research Engineer ($272,100 median, 227 roles); AI Engineering Manager ($244,000 median, 23 roles).
Demand for AI/ML Engineers has been strong and consistent. Unlike some AI roles that spike with hype cycles, ML engineering is a foundational need. Every company deploying AI models needs people who can keep them running, and the gap between research prototypes and production systems keeps growing.
The AI Job Market Today
The AI job market spans 4,317 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (3,004), Data Scientist (345), AI Software Engineer (309). These three account for the majority of open positions, though smaller categories often have higher per-role compensation because of specialized skill requirements.
The seniority mix tells a story about where AI teams are in their maturity. Entry-level roles (138) are outnumbered by mid-level (2,071) and senior (1,655) positions, reflecting that most companies are past the 'build a team from scratch' phase and need experienced engineers who can ship production systems. Leadership roles (Director, VP, C-Level) total 453 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (635 positions), with 3,657 requiring on-site or hybrid attendance. The remote share has stabilized after the post-pandemic correction. Senior and specialized roles (Research Scientist, ML Architect) are more likely to be remote-eligible than entry-level positions, partly because experienced hires have more negotiating power and partly because these roles require less hands-on mentorship.
AI compensation is structured in clear tiers. The market median sits at $215,000. Top-quartile roles start at $266,300, and the 90th percentile reaches $320,790. These figures include base salary with disclosed compensation. Total compensation (including equity, bonuses, and sign-on) runs 20-40% higher at companies that offer those components.
Category matters for compensation. AI Safety roles lead at $287,500 median, while Prompt Engineer roles sit at $145,000. The spread between highest and lowest-paying categories reflects the premium on specialized technical skills versus broader analytical roles.
The most in-demand skills across all AI postings: Python (2,249 postings), Aws (1,224 postings), Azure (938 postings), Rag (915 postings), Gcp (660 postings), Pytorch (640 postings), Prompt Engineering (624 postings), Kubernetes (559 postings). Python dominates, appearing in the vast majority of role descriptions regardless of category. Cloud platform experience (AWS, GCP, Azure) is the second most common requirement. The newer entrants to the top skills list (RAG, vector databases, LLM APIs) reflect the shift from traditional ML toward generative AI applications.
Frequently Asked Questions
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.