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About This Role
PURPOSE OF POSITION:
Serves as the senior administrative leader for the Maintenance and Mechanical Departments ensuring all administrative functions are completed effectively and efficiently. Exercises discretion and independent judgment on matters of significance, including interpreting policies, managing administrative operations, managing administrative staff, and serving as an advisor to the Chief Maintenance and Mechanical Officer (CMMO). This position ensures the effective execution of high\-level administrative functions, development of administrative programs, and alignment of departmental operations with ARRC strategic and operational goals. Duties and Responsibilities:
Plans, organizes, directs, and reviews the daily work and operations of six administrative assistants and timekeeper(s). Establishes priorities, assigns work, reviews performance, and ensures compliance with ARRC policies and procedures, and collective bargaining agreements. Responsible for maintaining a high level of team performance and competency by providing coaching, technical support, coordinating ongoing team member development and training, establishing goals, and monitoring performance.
Responsible for cross\-training of direct reports to ensure continuity of administrative operations.
Organizes own work, sets priorities and meets critical deadlines.
Responsible for management of apartment lease contracts. Provides direct oversight of lodging reservation process and assists direct reports in making lodging reservations as necessary.
Participates in departmental planning related to staffing, budgeting, resource allocation, and process improvements.
Compiles and maintains records, reports, budgets, forms, schedules and online documentation.
Exercises meaningful influence over hiring, discipline, and performance actions.
Active supervision of flagging process.
Utilizes advanced office software to produce complex documents, analytics, charts, and performance reports. Independently monitors and tracks departmental directives, commitments, and deadlines. Exercises independent judgment in resolving administrative issues and recommending process or policy improvements.
Researches, compiles, and prepares documents and briefings.
Coordinates directives and follows up on assignments.
Oversees creation and maintenance of administrative records which may include procurement documentation such as requisitions and quotes, reconciliation of department credit card (p\-card) purchases, travel records, and cost\-coding structures. Serves as the Department liaison with Supply Management for contract issuance. Reviews and approves invoices and expense reports within designated authority. Ensures accuracy and compliance with ARRC records management standards and procurement practices. Designs and implements administrative procedures, guidelines, and workflow systems.
Supports recruitment and training programs for Maintenance and Mechanical departments. Monitors employee training for completion. Ensures that training records are stored in ARRC repository.
Provides relief coverage for coworkers during periods of absence. Coordinates relief coverage for direct reports during absences to ensure continuity of operations.
Performs other duties as directed
FACTOR 1: Technical and Operational Knowledge. Advanced knowledge of administrative management principles, organizational systems, and records management. Knowledge of ARRC procurement processes, cost\-coding practices (operating and capital), and collective bargaining agreements. Solid understanding of budget management, including identification of operating expenses and capital expenses, and the ability to differentiate between ARRC capital funding and federal capital funding. Proficiency in Microsoft Office Suite, databases, reporting tools, and document management systems. Expertise in policy interpretation, administrative program execution, and business writing. Operating knowledge of Maintenance of Way timekeeping process sufficient to cover Timekeeper absences and to cross\-train staff. Railroad and operational field experience preferred.
FACTOR 2: Analytical Skills and Impact. Ability to interpret policies and exercise independent judgement in resolving complex administrative issues. Strong analytical, problem\-solving, and decision\-making skills with the ability to manage competing priorities. Detail\-oriented with the ability to design administrative workflows and evaluate process efficiency.
FACTOR 3: Supervision and Control. Direct supervision of represented administrative staff and oversight of administrative work product. Authority to influence hiring, discipline, and evaluation of performance. Oversight of administrative budgets, records, cost\-coding, flagging process, and procurement\-related processes.
FACTOR 4: Communication. Excellent interpersonal, written and verbal communication skills. Frequent interaction with executives, staff, vendors, and external customers. Ability to gain cooperation and support from others through persuasion and relationship\-building. Ability to maintain confidentiality at all times.
FACTOR 5: Working Conditions. Work is performed in a standard office or indoor environment. Essential functions are regularly performed without exposure to adverse environmental conditions; however, employees may be exposed to minor inconveniences such as occasional heating/cooling, or ventilation problems. Occasional rail belt exposure and travel for meetings, outreach, and training. On\-call as part of the Incident Command Team.
Minimum Qualifications
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Education Requirements:
Associate degree in business administration, management, organizational leadership, public administration, or related field. May substitute related work experience for the educational requirement on a year\-for\-year basis.
Work Experience:
Five (5\) years of progressively responsible office management experience.
Three (3\) years of supervisory experience overseeing administrative or operational support teams.
Experience in policy interpretation and administrative systems management.
Experience with records management programs and procurement processes.
Extensive knowledge of office practices and related software programs.
Must have valid driver’s license and maintain confidentiality.
Preferred Qualifications
Bachelor’s degree in business administration, management, organizational leadership, public administration, or related field
Railroad and operational field experience
Certified Administrative Professional (CAP), Certified Project Management Professional (PMP), or related professional certification
Additional Required Information
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Please include any REQUIRED AND DESIRED QUALIFICATIONS in your APPLICANT PROFILE and/or RESUME. If using work experience not already documented in your application, also provide the employer name, your job title, dates of employment and whether full\- or part\-time. Your application will be closely reviewed to determine if the responses are supported and minimum qualifications are clearly met. If they are not, the applicant will not advance to the interview and selection phase of the recruitment.
Contact Information
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Alaska Railroad Human Resources Department
E\-Mail: arjobinfo@akrr.com
Phone: 907\-265\-2438
Mailing Address: P.O. Box 107500, Anchorage, AK 99510\-7500
Street Address: 327 West Ship Creek, Anchorage, AK
Fax Number: (907\) 265\-2542
Alaska Railroad Corporation is an equal opportunity employerWORKPLACE ALASKA APPLICATION QUESTIONS \& ASSISTANCE
Questions regarding application submission or system operation errors should be directed to the Workplace Alaska hotline at 1\-800\-587\-0430 (toll free) or (907\) 465\-4095 if you are located in the Juneau area. Requests for information may also be emailed to recruitment.services@alaska.gov.
For applicant password assistance please visit:https://www.governmentjobs.com/OnlineApplication/User/ResetPassword
Alaska Railroad Corporation Benefits
The following briefly describes the main benefits available to regular employees of the Alaska Railroad Corporation. Actual benefits differ by bargaining unit.
Retirement Plans
ARRC Pension Plan – Participation is mandatory. You are automatically enrolled in the Plan when you meet the eligibility requirement of your bargaining unit. Employees contribute 9% of their Earnings on a pre\-tax basis. The Railroad is exempt from participation in Social Security; however, Medicare Tax is withheld. Participants vest with 5 years of eligible Vesting Service which entitles one to receive a pension benefit at retirement age.
Tier 2 Description (Employees hired after July 1, 2015\)
Normal Retirement Age is age 65, however, the plan allows one to retire as early as age 60\. The formula for a monthly Normal Retirement Benefits is 2% x Final Average Earnings x all Credited Service.
Early retirement, survivor and disability benefits are available for vested participants.
401(k) Tax Deferred Savings Plan – Participation is optional. You may enroll once you meet the eligibility requirement of your bargaining unit. Depending on the bargaining unit, there may be an employer match.
457 Deferred Compensation Plan – Participation is optional for non\-represented employees.
Insurance and Flexible Spending Plans
All plans are optional except the RR Dental Plan for bargaining unit employees.
Health Insurance Plan
A comprehensive health insurance plan, self\-insured by the ARRC and administered by Premera Blue Cross Blue Shield of Alaska. Coverage is also available for the employee’s spouse and dependent children. ARRC and the participant share the premium cost. Bargaining unit employees are Eligibility after 90 days, and non\-represented employees are eligible as of the date of hire.
The Railroad offers a Prefered Provider Organization plan (PPO Blue Essentials) and a Consumer Directed Healthcare Plan with a Health Saving Account (Gold Essentials). The Plans have the following features.
The Railroad also offers two dental plans.
The Railroad National Dental for represented employees.
The Alaska Railroad Optional Dental Plan for both represented and non\-represented employees.
Paid Leave \& Holidays
Vacation Leave –accrual per bi\-weekly pay period:
Represented Employees
0\-3 Years of Service \= 4 Hours
\>3\-15 Years of Service \= 6 Hours
\>15 Years of Service \= 8 Hours
Non\-Represented Employees
0\-3 Years of Service \= 6 Hours
\>3\-15 Years of Service \= 8 Hours
\>15 Years of Service \= 10 Hours
Sick Leave: accrues at 4 hours (Represented) or 2 hours (Non\-Represented) per pay period.
11 Paid holidays
For additional information regarding these benefits, please go to www.alaskarailroad.com
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 26,159 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At State of Alaska, 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 $166,983 based on 13,781 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $131,300.
Across all AI roles, the market median is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Architect ($292,900). By seniority level: Entry: $76,880; Mid: $131,300; Senior: $227,400; Director: $244,288; VP: $234,620.
State of Alaska AI Hiring
State of Alaska has 4 open AI roles right now. They're hiring across AI/ML Engineer. Positions span Anchorage, AK, US, Fairbanks, AK, US, Juneau, AK, US. Compensation range: $47K - $47K.
Location Context
Across all AI roles, 7% (1,863 positions) offer remote work, while 24,200 require on-site attendance. Top AI hiring metros: Los Angeles (1,695 roles, $178,000 median); New York (1,670 roles, $200,000 median); San Francisco (1,059 roles, $244,000 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 26,159 open positions tracked in our dataset. By seniority: 2,416 entry-level, 16,247 mid-level, 5,153 senior, and 2,343 leadership roles (Director, VP, C-Level). Remote roles make up 7% of the market (1,863 positions). The remaining 24,200 roles require on-site or hybrid attendance.
The market median for AI roles is $184,000. Top-quartile compensation starts at $244,000. The 90th percentile reaches $309,400. Highest-paying categories: AI Engineering Manager ($293,500 median, 28 roles); AI Architect ($292,900 median, 108 roles); AI Safety ($274,200 median, 19 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 26,159 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (23,752), AI Software Engineer (598), AI Product Manager (594). 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 (2,416) are outnumbered by mid-level (16,247) and senior (5,153) 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 2,343 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 7% of all AI roles (1,863 positions), with 24,200 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 $184,000. Top-quartile roles start at $244,000, and the 90th percentile reaches $309,400. 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 Engineering Manager roles lead at $293,500 median, while Prompt Engineer roles sit at $122,200. 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 (16,749 postings), Aws (8,932 postings), Rust (7,660 postings), Python (3,815 postings), Azure (2,678 postings), Gcp (2,247 postings), Prompt Engineering (1,469 postings), Openai (1,269 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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