Interested in this AI/ML Engineer role at GKN Aerospace?
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About This Role
Fantastic challenges. Amazing opportunities.
GKN Aerospace is reimagining air travel: going further, faster and greener! Fuelled by great people whose expertise and creativity sets the standards in our industry, we’re inspired by the opportunities to innovate and break boundaries. We’re proud to play a part in protecting the world’s democracies. And we’re committed to putting sustainability at the centre of everything we do, opening up and protecting our planet. With over 16,000 employees across 33 manufacturing sites in 12 countries we serve over 90% of the world’s aircraft and engine manufacturers and achieved sales of £3.35 bn.in 2023. There are no limits to where you can take your career.
Job Summary
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The purpose of this role is to manage the allocated program in order to make sure all targets and commitments are met both to internal as well as external customers.
The Program Manager coordinates with Operations, Engineering and/or other disciplines to ensure that the resources required to meet program obligations are available.
The Program Manager manages the tactical/operational relationship with the customer whereas the BD organization manages the strategic relationship with the customer.
Job Responsibilities
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- Responsible for executing the program (including changes) making sure it is compliant with all approved business cases and contractual requirements, both during the NPI phase as well as in production
- Responsible for delivering financial (sales, profit etc.) targets of the program
- Making sure NPI projects are delivered on time and on budget in accordance with approved business cases
- Responsible for continuously monitoring the performance of the program, managing off-track items when needed and for reporting progress through the BR5 process
- Driving program improvement plans including cost improvement, pricing initiatives, zero defect initiatives etc. in coordination with relevant stakeholders
- Supports the SD/VP in defining the vision, strategy, budget for the program to optimize cash flow, profitability and growth
- Responsible for undertaking any other activity required to ensure successful delivery of the program
- Acts as the voice of the customer internal GKN when needed:
+ *Representing the customers’ interests in internal communications*
+ *Ensure warranty returns are managed efficiently*
+ *Ensure any request by the customer is closed out in a timely manner*
- Act as GKN’s voice towards the customer when needed:
+ *Simplifying and coordinating communications to ensure a consistent message in communications to customers*
+ *Supporting operations or any other function by ensuring timely progress of* *activities required by the customer to fulfill our obligations*
- Continuously look to develop and grow the program further:
+ *Take lead on all new rfq’s making sure we submit competitive proposals/offerings on time*
+ *Work with the site teams, the commercial team, engineering etc. to secure new business bids*
+ *Be proactive in what we can offer the customers by having knowledge of our capabilities across all business lines and how that could turn into product offerings*
+ *Full understanding and support of our technology development activities so that those can turn into future business opportunities*
- Understand day to day business across all our sites, understand possibilities and challenges to be able to improve the program
- Adhere to all program management standards and policies in accordance with the GKN Aerospace Program Management framework
Contribute to the GKN Aerospace Program Management process development when needed
Job Qualifications
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Required Qualifications:
- Bachelor’s Degree (Engineering, Business, Management, or applicable field)
- 5+ years of Program Management experience within the manufacturing industry, preferably aerospace and/or defence.
- Must be a US Citizen due to program security clearance requirements and/or SSA requirements.
- Ability to create, manage and execute a project plan utilizing MS Project or other tools
- Strong communication skills
- Ability to achieve by influencing others
- Experience in commercial, engineering or operations within the Aerospace industry
- Ability to build relationships with customers and other external stakeholders
- Financial acumen:
+ *Ability to understand P&L / Cashflow statement*
+ *Understand our financial BC model for bids/rfq’s*
+ *Understand our CAPEX process*
Preferred Qualifications:
- GKN Aerospace experience
- MRO business experience
- Either completed or registered for acknowledged Program Management Certification
Travel Requirement:
- Frequent travel to the sites and customer locations. Domestic travel as required for customer meetings and internal leadership meetings; estimated travel 30%.
Compensation Range
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The compensation range for this position is between $120,000 - $150,000.
We’ll offer you fantastic challenges and amazing opportunities. This is your chance to be part of an organisation that has proven itself to be at the cutting edge of our industry; and is committed to pushing the boundaries even further. And with some of the best training on offer in the industry, who knows how far you can go?
A Great Place to work needs a Great Way of Working
Everyone is welcome to apply to GKN. We believe that we can only achieve our ambitions through a coming together of diverse minds who enjoy collaborating in an inspirational environment. Through our commitment to diversity, inclusion and belonging and by living our five powerful principles we’ve created a culture where everyone feels welcome to contribute. It’s a culture that won us ‘The Best Workplace Culture Award’. By embracing and celebrating what makes us unique we encourage everyone to bring their full self to work.
We’re also committed to providing an accessible recruitment process, so if you require reasonable adjustments at any stage during our recruitment process please get in touch and let us know.
We are the place where human dreams, plus human endeavour, shape the future of aerospace innovation and technology.
Salary Context
This $120K-$150K range is below the median for AI/ML Engineer roles in our dataset (median: $170K across 217 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 33,423 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At GKN Aerospace, 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 $154,000 based on 8,743 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $147,000. This role's midpoint ($135K) sits 12% below the category median. Disclosed range: $120K to $150K.
Across all AI roles, the market median is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $85,000; Mid: $147,000; Senior: $225,000; Director: $230,600; VP: $248,357.
GKN Aerospace AI Hiring
GKN Aerospace has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in El Cajon, CA, US. Compensation range: $150K - $150K.
Location Context
Across all AI roles, 7% (2,320 positions) offer remote work, while 30,984 require on-site attendance. Top AI hiring metros: New York (1,633 roles, $204,100 median); Los Angeles (1,356 roles, $179,440 median); San Francisco (1,230 roles, $240,000 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 33,423 open positions tracked in our dataset. By seniority: 3,283 entry-level, 20,769 mid-level, 6,381 senior, and 2,990 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,320 positions). The remaining 30,984 roles require on-site or hybrid attendance.
The market median for AI roles is $190,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $300,688. Highest-paying categories: AI Engineering Manager ($293,500 median, 21 roles); AI Safety ($274,200 median, 24 roles); Research Engineer ($260,000 median, 264 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 33,423 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (30,275), AI Software Engineer (749), AI Product Manager (741). 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 (3,283) are outnumbered by mid-level (20,769) and senior (6,381) 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 2,990 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,320 positions), with 30,984 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 $190,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $300,688. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $145,600. 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: Rag (21,235 postings), Aws (11,126 postings), Rust (9,803 postings), Python (4,999 postings), Azure (3,220 postings), Gcp (2,707 postings), Prompt Engineering (1,817 postings), Openai (1,487 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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