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About This Role
Job Description
We're seeking an action\-oriented engineer with intellectual curiosity who is excited to put their potential to use testing space flight hardware. The position will be as part of a spacecraft / space vehicle test team as a test lead, with a focus on testing execution of flight hardware.
As a Senior Principal Engineer at BAE Systems Space \& Mission Systems (SMS) you will lead and mentor team members within the field. You will have the opportunity to:
- Lead or support significant test campaigns on a large bus and space vehicle program.
- Develop and support new business pursuits.
- Take responsibility as a lead for strengthening and supporting the company’s strategic goal.
This is a challenging, fast\-paced job which will be exciting and highly gratifying for the successful candidate.
The Engineering, Science and Analysis (ESA) Strategic Capabilities Unit comprises the technical talent and organizational leadership that enables the successful delivery of high\-impact discriminating technologies for our customers' missions. Our collaborative, cross\-functional teams are committed to innovation, integrity, continual learning, and strong execution. What You’ll Do:
- Work in fast\-paced team environments assisting in the integration and testing of spacecraft hardware.
- Work in cleanroom and lab environments to verify hardware meets requirements and characterize/calibrate its performance.
- Leverage and grow a detailed understanding of spacecraft systems, subsystems, space vehicles, and launch operations.
- Write, review, and update proposal responses and study reports with a focus on AI\&T for spacecraft buses and integrated space vehicles.
- Define program integration and test approach and generate AI\&T flows.
- Identify GSE, facilities, and equipment required for AI\&T and launch operations.
- Provide cost and schedule estimates for spacecraft assembly, integration, test, and launch operations.
- Evaluate contractual documents and requirements for AI\&T impact.
- Identify creative solutions to reduce cost, schedule, and risk for AI\&T.
- Make defendable decisions and adapt to changing circumstances.
- Leadership Responsibilities:
+ Provide strategic direction and oversight for AI\&T operations.
+ Lead a high\-performing team of engineers and technicians.
+ Foster a culture of excellence, collaboration, and continuous improvement.
+ Develop and implement a comprehensive technical vision for AI\&T.
+ Establish and track key performance metrics.
- Additional Responsibilities:
+ Mentor and develop team members.
- Maintain a regular and predictable work schedule.
- Establish and maintain effective working relationships within the department, the Strategic Business Units, Strategic Capabilities Units and the Company. Interact appropriately with others in order to maintain a positive and productive work environment.
- Perform other duties as necessary.
On\-Site Work Environment: This position requires regular in\-person engagement by working on\-site five days each normally scheduled week in the primary work location. Travel and local commute between company campuses and other possible non\-company locations may be required.
Working Conditions:
- Work is performed in an office, laboratory, production floor, or cleanroom, outdoors or remote research environment.
- May occasionally work in production work centers where use of protective equipment and gear is required.
- May access other facilities in various weather conditions.
Required Education, Experience, \& Skills
- BS degree or higher in Engineering or a related technical field is required plus 8 or more years related experience.
- Each higher\-level degree, i.e., Master’s Degree or Ph.D., may substitute for two years of experience. Related technical experience may be considered in lieu of education. Degree must be from a university, college, or school which is accredited by an agency recognized by the US Secretary of Education, US Department of Education.
- Experience in the testing of spacecraft, space vehicles, and their related components and systems.
- Experience in spacecraft RF testing, performing end\-to\-end validation of the RF system.
- Experience with spacecraft command and control systems, simulators, software test benches and other electrical ground support equipment.
- Experience with software in support of testing.
- Experience and interest in cost and schedule estimation activities and proposal efforts and / or IRAD activities.
- Presentation and communication skills.
- Understand test processes including defining test strategies, test plans, and test procedures.
- Attention to detail while appreciating the bigger picture of the complex and ambitious projects that we take on at BAE Systems SMS.
- Proficient in MS Office tools and have computer skills.
\#LI\-AP1
A security clearance or access with Polygraph is not required to be eligible for this position. However, the applicant must be willing and eligible for submission, depending on program requirements, after an offer is accepted and must be able to maintain the applicable clearance/access.
Preferred Education, Experience, \& Skills
- Knowledge and test experience using test automation applications and tools.
- Demonstrated, mentoring, leadership and team building skills.
- Familiarity with software testing at various levels, unit, integration, end\-to\-end.
- Proficiency in one or more of the following programming languages: JavaScript, Python, Ruby, or Go.
- Experience with COSMOS Command and Control Software.
- Experience with GitLab.
- Familiarity with software unit testing.
- Direct experience with setting up and configuring RF GSE, including familiarity with testing measurement tools (signal generators, spectrum analyzers, power meters).
- Understanding of telecommunication protocol practices, including familiarity with industry standards and best practices.
- Experience working with common frequency bands, examples: KA, X, S bands.
- Identify and mitigate technical and schedule risks, ensuring the delivery of high\-quality products and services.
- Drive business growth through innovative solutions, process improvements, and strategic partnerships.
- Develop and manage budgets, ensuring cost\-effective delivery of AI\&T services.
- Negotiate and manage contracts, ensuring compliance with contractual obligations and customer requirements.
- Lead change management initiatives, ensuring seamless transition to new processes, technologies, or organizational structures.
- Space or military experience.
Pay Information
Full\-Time Salary Range: $132962 \- $226035
Please note: This range is based on our market pay structures. However, individual salaries are determined by a variety of factors including, but not limited to: business considerations, local market conditions, and internal equity, as well as candidate qualifications, such as skills, education, and experience.
Employee Benefits: At BAE Systems, we support our employees in all aspects of their life, including their health and financial well\-being. Regular employees scheduled to work 20\+ hours per week are offered: health, dental, and vision insurance; health savings accounts; a 401(k) savings plan; disability coverage; and life and accident insurance. We also have an employee assistance program, a legal plan, and other perks including discounts on things like home, auto, and pet insurance. Our leave programs include paid time off, paid holidays, as well as other types of leave, including paid parental, military, bereavement, and any applicable federal and state sick leave. Employees may participate in the company recognition program to receive monetary or non\-monetary recognition awards. Other incentives may be available based on position level and/or job specifics.
About BAE Systems Space \& Mission Systems
BAE Systems, Inc. is the U.S. subsidiary of BAE Systems plc, an international defense, aerospace and security company which delivers a full range of products and services for air, land and naval forces, as well as advanced electronics, security, information technology solutions and customer support services. Improving the future and protecting lives is an ambitious mission, but it’s what we do at BAE Systems. Working here means using your passion and ingenuity where it counts – defending national security with breakthrough technology, superior products, and intelligence solutions. As you develop the latest technology and defend national security, you will continually hone your skills on a team—making a big impact on a global scale. At BAE Systems, you’ll find a rewarding career that truly makes a difference.
Headquartered in Boulder, Colorado, Space \& Mission Systems is a leading provider of national defense and civil space applications, advanced remote sensing, scientific and tactical systems for government and commercial customers. We continually pioneer ways to innovate spacecraft, mission payloads, optical systems, and other defense and civil capabilities. Powered by endlessly curious people with an unwavering mission focus, we continually discover ways to enable our customers to perform beyond expectation and protect what matters most.
This position will be posted for at least 5 calendar days. The posting will remain active until the position is filled, or a qualified pool of candidates is identified.
Multiple positions may be available on this opening.
Salary Context
This $132K-$226K range is above the median for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At BAE Systems USA, 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 $218,750 based on 3,817 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $230,000. This role's midpoint ($179K) sits 18% below the category median. Disclosed range: $132K to $226K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
BAE Systems USA AI Hiring
BAE Systems USA has 2 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Falls Church, VA, US, Boulder, CO, US. Compensation range: $226K - $340K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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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