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About This Role
At Boeing, we innovate and collaborate to make the world a better place. We’re committed to fostering an environment for every teammate that’s welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us.
At Boeing, we innovate and collaborate to make the world a better place. We’re committed to fostering an environment for every teammate that’s welcoming, respectful and inclusive, with great opportunity for professional growth. Find your future with us.
The Boeing Company is looking for a Senior AI Software Engineer to join the Boeing AI & Autonomy Applications and Innovations team in Berkeley, MO.
Our teams are currently hiring for a broad range of experience levels including: Experienced and Senior Level Software Engineers.
Employees work in a dynamic and distributed environment where the initiative and contribution of each team member is critical to success. The ideal candidate will be able to work independently and as part of a distributed (and international) team. Many projects are multi-year and end with the successful transition and integration of new capabilities to Boeing end-product deployment. Project work can be funded by Independent Research and Development, Contracted Research and Development, or support to an internal Business Unit.
A successful candidate will be a highly motivated Senior AI Software Engineer with software development, AI application, and machine learning knowledge. They will have experience with Computer Vision, Generative AI, native mobile application (iOS/Android), and web-based solution development in an agile environment. They will participate in the research and development as well as the rapid prototyping of advanced computing technologies for aerospace products and services.
They will be comfortable in taking initiative, learning by experience, possess an interest in personal learning, seek feedback from others, and creating innovative ideas. They will get great satisfaction in engineering and applying solutions that will work in the real world.
Position Responsibilities:
- Provides solutions to a variety of technical problems of moderate scope and complexity.
- Works under general supervision, and no instructions are needed for routine work.
- Leverages knowledge of Artificial Intelligence, Machine Learning and data mining approaches and techniques to build software applications that drive measurable improvements.
- Effectively communicates results to teammates and customers.
- Seeks feedback from multiple sources to improve and develop.
Basic Qualifications (Required Skills/ Experience):
- Bachelor of Science degree or higher
- Experience preparing data for, developing and evaluating learned models
- Experience with programming languages and data tools such as Python, Matlab, C++, C or Java as well as SQL, Teradata, Tableau, Gephi or Airflow.
Preferred Qualifications (Desired Skills/Experience):
- Master of Science in Engineering, Computer Science, Data Science or similar
- 5+ years relevant experience including jobs, internships, and assistantships
- Experience with Machine Learning development and deployment pipeline, i.e. from data to model
- Experience with Agile methodology and repositories, such as ADO, JIRA and Git
Additional Preferred Qualifications:
- PhD in Engineering, Computer Science or Data Science
- Experience with Product Management and turning customer requirements into deployed solutions.
Travel:
Position may require travel up to 10% of the time.
Drug Free Workplace:
Boeing is a Drug Free Workplace (DFW) where post offer applicants and employees are subject to testing for marijuana, cocaine, opioids, amphetamines, PCP, and alcohol when criteria is met as outlined in our policies.
Pay & Benefits:
At Boeing, we strive to deliver a Total Rewards package that will attract, engage and retain the top talent. Elements of the Total Rewards package include competitive base pay and variable compensation opportunities.
The Boeing Company also provides eligible employees with an opportunity to enroll in a variety of benefit programs, generally including health insurance, flexible spending accounts, health savings accounts, retirement savings plans, life and disability insurance programs, and a number of programs that provide for both paid and unpaid time away from work.
The specific programs and options available to any given employee may vary depending on eligibility factors such as geographic location, date of hire, and the applicability of collective bargaining agreements.
Pay is based upon candidate experience and qualifications, as well as market and business considerations.
Summary Pay Range for Senior Level (Level 3): $140,250 - $189,750
Summary Pay Range for Senior Level (Level 4): $173,400 - $234,600
Applications for this position will be accepted until Oct. 15, 2026
Export Control Requirements:
This position must meet U.S. export control compliance requirements. To meet U.S. export control compliance requirements, a “U.S. Person” as defined by 22 C.F.R. §120.62 is required. “U.S. Person” includes U.S. Citizen, U.S. National, lawful permanent resident, refugee, or asylee.
Export Control Details:
US based job, US Person required
Education
Bachelor's Degree or Equivalent Required
Relocation
Relocation assistance is not a negotiable benefit for this position.
Visa Sponsorship
Employer will not sponsor applicants for employment visa status.
Shift
This position is for 1st shift
Equal Opportunity Employer:
Boeing is an Equal Opportunity Employer. Employment decisions are made without regard to race, color, religion, national origin, gender, sexual orientation, gender identity, age, physical or mental disability, genetic factors, military/veteran status or other characteristics protected by law.
Your Benefits
No matter where you are in life, our benefits help prepare you for the present and the future.
- Generous company match to your 401(k).
- Industry-leading tuition assistance program pays your institution directly.
- Fertility, adoption, and surrogacy benefits.
- Up to $10,000 gift match when you support your favorite nonprofit organizations.
These programs are subject to eligibility requirements and other conditions, which may differ for employees of certain subsidiaries or business units, or union-represented employees depending on bargaining agreement terms. If this information conflicts with the program documents, the latter shall control. This material is informational only.
Salary Context
This $140K-$234K range is above the median for AI/ML Engineer roles in our dataset (median: $178K across 1623 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 9,079 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Boeing, 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 $211,950 based on 13,048 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $229,300. This role's midpoint ($187K) sits 12% below the category median. Disclosed range: $140K to $234K.
Across all AI roles, the market median is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. For comparison, the highest-paying categories include AI Safety ($256,000) and Research Engineer ($252,000). By seniority level: Entry: $111,000; Mid: $193,200; Senior: $229,300; Director: $272,300; VP: $235,830.
Boeing AI Hiring
Boeing has 4 open AI roles right now. They're hiring across AI/ML Engineer, Data Engineer, Data Scientist. Positions span Berkeley, MO, US, Washington, DC, VA, US. Compensation range: $234K - $250K.
Location Context
Across all AI roles, 6% (531 positions) offer remote work, while 8,478 require on-site attendance. Top AI hiring metros: New York (3,078 roles, $221,000 median); San Francisco (2,646 roles, $261,000 median); Los Angeles (1,486 roles, $210,000 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 9,079 open positions tracked in our dataset. By seniority: 106 entry-level, 4,384 mid-level, 3,343 senior, and 1,246 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (531 positions). The remaining 8,478 roles require on-site or hybrid attendance.
The market median for AI roles is $213,000. Top-quartile compensation starts at $263,911. The 90th percentile reaches $318,400. Highest-paying categories: AI Safety ($256,000 median, 66 roles); Research Engineer ($252,000 median, 457 roles); AI Engineering Manager ($251,622 median, 55 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 9,079 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (6,862), AI Product Manager (453), AI Software Engineer (451). 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 (106) are outnumbered by mid-level (4,384) and senior (3,343) 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 1,246 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (531 positions), with 8,478 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 $213,000. Top-quartile roles start at $263,911, and the 90th percentile reaches $318,400. 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 $256,000 median, while Prompt Engineer roles sit at $141,440. 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 (1,649 postings), Aws (898 postings), Azure (723 postings), Rag (671 postings), Gcp (536 postings), Pytorch (434 postings), Claude (410 postings), Kubernetes (406 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
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