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About This Role
Job Title: Falcon 2000 LX Captain
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Location: Denver, CO (APA)
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About George J. Priester Aviation
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George J. Priester Aviation is a premier aviation services company providing comprehensive aircraft management, charter, maintenance, and flight operations solutions. With decades of experience supporting owner-managed and client-focused flight departments, we are known for our commitment to safety, professionalism, and white-glove service.
Our team operates in a dynamic Part 135 and Part 91 environment, supporting diverse aircraft types and mission profiles across the U.S. and internationally. At George J. Priester Aviation, we value integrity, collaboration, and accountability and we take pride in building long-term careers within aviation.
Position Summary:
The Pilot in Command (PIC) is responsible for the safe and efficient operation of assigned aircraft, ensuring compliance with all applicable Federal Aviation Regulations (FARs), company policies, and operational procedures. The PIC will manage all aspects of flight preparation and execution, including crew coordination, risk management, and passenger service. This role requires exceptional leadership, technical expertise, and a strong focus on safety and customer service. The PIC serves as the final authority on all decisions regarding the aircraft and its operation.
Pilot Schedule & Program Overview
This position supports a 135-operation flying a Falcon 2000 LX based out of APA. The typical schedule is 8 hard days off a month, with average annual flight time of approximately 300 hours (220 hours owner flying and 80 hours charter flying approximately). The operation is a 2- pilot crew and 1 maintenance crew chief and primarily conducts domestic flights and some international flights. This information is provided for planning purposes and may vary based on operational demands and regulatory considerations.
Key Responsibilities:
- Flight Operations: Act as the Pilot in Command, assuming final authority for the safe operation of the aircraft on all assigned flights. Ensure compliance with all FAA regulations, company flight operations manuals, and standard operating procedures.
- Pre-flight Planning: Conduct thorough pre-flight planning, including weather analysis, performance calculations, routing, fuel planning, and aircraft airworthiness checks. Ensure that all flight preparations are in line with company and regulatory standards.
- Crew Resource Management (CRM): Maintain a high level of crew coordination and communication throughout all phases of flight. Lead the crew in performing duties in a professional, efficient, and cooperative manner, fostering a culture of teamwork and safety.
- Passenger Service: Provide the highest level of customer service, ensuring the safety, comfort, and satisfaction of passengers. Serve as the primary point of contact for clients during the flight, addressing any concerns or special requests.
- Safety Management: Actively engage in the company’s Safety Management System (SMS), promoting a proactive safety culture. Identify and mitigate risks using risk analysis tools, and participate in safety audits and corrective action processes.
- Mentorship & Leadership: Mentor and guide First Officers and other flight crew members. Ensure that all crew members understand their roles and responsibilities, providing clear direction and feedback to foster professional growth.
- Post-flight Duties: Complete all required post-flight documentation, including trip reports, logbook entries, and any maintenance or operational notes. Report any safety concerns or equipment issues to the maintenance team.
- Regulatory Compliance: Ensure that all flight operations comply with FAA regulations, including maintaining currency with required training, medical certifications, and company policies. Keep flight crew records up to date.
Qualifications:
- Flight Experience:
+ Minimum 5000 total flight hours.
+ 2500 hours as Pilot in Command (PIC).
+ 2500 hours multi-engine land, with 1500 hours as multi-engine PIC.
+ 2000 hours in turbine aircraft and 500 hours instrument time.
- Certifications:
+ Airline Transport Pilot (ATP) certificate with multi-engine land rating required.
+ Current First-Class Medical Certificate required.
+ FCC Restricted Radiotelephone Operator’s Permit preferred.
- Skills:
+ Strong knowledge of FAA regulations, flight planning, and safety management systems.
+ Excellent communication and leadership skills, with the ability to make sound decisions under pressure.
+ Proficient in the use of flight planning and aviation management software.
- Preferred Experience:
+ Previous experience in Part 135 operations is highly desirable.
This is an exempt position which requires flexibility to meet the demands of business.
Compensation & Benefits
George J. Priester Aviation offers a competitive total rewards package designed to support the health, financial security, and well-being of our team members, including:
Health & Wellness
- Medical coverage (PPO and High Deductible plans) through Blue Cross Blue Shield
- Dental and vision coverage
- Company-paid short-term and long-term disability insurance
- Company-paid basic life and AD&D insurance, with optional supplemental coverage
- Voluntary accident, critical illness, and hospital indemnity plans
Financial & Retirement
- 401(k) retirement plan with company match
- Annual company-funded profit-sharing contribution
- Health Savings Account (HSA), Flexible Spending Accounts (FSA), and Dependent Care FSA options
Time Off & Work-Life Balance
- Paid company holidays
- Unlimited Paid Time Off (PTO), subject to scheduling guidelines
- Sick leave in accordance with company policy
Additional Benefits
- Tuition reimbursement program
- Company-paid legal services and identity theft protection
- Company-paid pet insurance for dogs or cats
- Employee assistance and support resources
*Benefits eligibility and offerings may vary based on role, employment type, and client program.*
Work Environment
This position operates in a fast-paced aviation environment that may include travel, variable schedules, and close coordination with flight crews, maintenance teams, and client representatives.
Equal Opportunity Employer
George J. Priester Aviation is an Equal Opportunity Employer and is committed to fostering an inclusive workplace. We do not discriminate based on race, color, religion, sex, sexual orientation, gender identity, national origin, age, disability, veteran status, or any other protected status.
How to Apply:
If you are ready to take your career to the next level and meet the qualifications for this role, we invite you to apply. Please submit your resume detailing your experience and why you are an excellent fit for this position.
Salary Context
This $250K-$290K range is above the 75th percentile 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 37,339 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Priester Holdings Llc, 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 ($270K) sits 75% above the category median. Disclosed range: $250K to $290K.
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.
Priester Holdings Llc AI Hiring
Priester Holdings Llc has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Englewood, CO, US. Compensation range: $290K - $290K.
Location Context
Across all AI roles, 7% (2,732 positions) offer remote work, while 34,484 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 37,339 open positions tracked in our dataset. By seniority: 3,672 entry-level, 23,272 mid-level, 7,048 senior, and 3,347 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (2,732 positions). The remaining 34,484 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 37,339 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (33,926), AI Software Engineer (823), AI Product Manager (805). 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 (3,672) are outnumbered by mid-level (23,272) and senior (7,048) 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 3,347 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (2,732 positions), with 34,484 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 (23,721 postings), Aws (12,486 postings), Rust (10,785 postings), Python (5,564 postings), Azure (3,616 postings), Gcp (3,032 postings), Prompt Engineering (2,112 postings), Kubernetes (1,713 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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