Interested in this AI/ML Engineer role at Ahtna, Incorporated?
Apply Now →About This Role
Summary
Ahtna, Incorporated is an Alaska Native Regional Corporation established under the Alaska Native Claims Settlement Act (ANCSA), representing Shareholders across the Ahtna region of Alaska. Guided by a mission to protect natural resources, preserve Ahtna culture and heritage, and improve Shareholder benefits, Ahtna oversees Shareholder services, lands and natural resource management, corporate communications, and regional partnerships across the Ahtna region. Ahtna is seeking a President to serve as the primary liaison to its Shareholders and provide executive oversight of key corporate functions, working hand-in-hand with the CEO and Board of Directors to advance the organization's long-range strategy.
Please Note: This position is open to Ahtna Shareholders only.
To be considered for this role, please apply online at https://www.peopleak.com/jobs (https://www.peopleak.com/jobs).
Essential Duties and Responsibilities
- Serve as the primary liaison between the Corporation and its Shareholders on services, enrollment, distributions, and benefits
- Provide executive oversight of the General Counsel, Chief Financial Officer, and assigned corporate functions (Legal, Compliance, Risk Management, Shareholder Services, Corporate Communications, and more)
- Lead strategic oversight of the region's lands and natural resources, and build relationships with tribal governments, village corporations, and regional stakeholders
- Partner with the CEO and Executive Management Team to align business strategy with the Corporation's ANCSA responsibilities
- Advise the Board of Directors on ANCSA matters, governance, enterprise risk, and long-range strategic planning
- Oversee corporate communications, including Shareholder newsletters, annual reports, and proxy materials
- Represent the Corporation at annual Shareholder meetings, village and community events, and regional forums
- Guide executive talent management across assigned functions, including succession planning and leadership development
Minimum Qualifications
- Bachelor's degree in a related field (Business, Public Administration, Finance, Law, Native Studies, etc.) + Education may be substituted for leadership experience on a 2:1 basis
- 10+ years of progressively responsible leadership or executive management experience
- 5+ years working with executive leadership teams, boards of directors, tribal councils, or similar governing bodies
- Shareholder of Ahtna, Incorporated
- Demonstrated experience overseeing multiple organizational functions or departments
- Knowledge of ANCSA, Alaska Native Corporation governance, and the region's communities, culture, and traditions
- Valid driver's license
Preferred Qualifications
- Master's degree in Business Administration, Public Administration, Finance, Law, Native Studies, or a related field
- Prior experience as a President, CEO, Executive Director, or comparable executive leader
- Background working within an Alaska Native Corporation environment
- Ability to obtain and maintain a U.S. Government security clearance, as required
Shareholder Preference
Pursuant to applicable law, preference will be given to qualified Ahtna Native Corporation Shareholders, Descendents, and Spouses in all phases of employment.
Physical Demands
Frequent sitting, using hands/fingers, handling, reaching with hands and arms, talking, hearing, and seeing (up close, at a distance, along the periphery, with depth perception, and the ability to adjust focus), occasional walking or standing, occasional lifting of up to 10 pounds.
Reasonable accommodations may be made to enable individuals with disabilities to perform the essential functions.
Work Environment
The work environment characteristics described in this job description are representative of those an employee encounters while performing the essential duties and responsibilities of this job. Work is performed in an office environment, may be subject to temperature and noise level changes.
Work Schedule : Monday – Friday 8:00 to 5:00, may vary based upon business needs
Experience
Required* 10 year(s): • Bachelor's degree in a related field (Business, Public Administration, Finance, Law, Native Studies, etc.) Education may be substituted for Leadership experience on a 2:1 basis • 10+ years of progressively responsible leadership or executive management experience • 5+ years working with executive leadership teams, boards of directors, tribal councils, or similar governing bodies • Shareholder of Ahtna, Incorporated
Education
Preferred* Bachelors or better in Business Administration or related field
Licenses & Certifications
Required* Driver's License
Equal Opportunity Employer/Protected Veterans/Individuals with Disabilities
This employer is required to notify all applicants of their rights pursuant to federal employment laws. For further information, please review the Know Your Rights (https://www.eeoc.gov/poster) notice from the Department of Labor.
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 9,653 AI roles we're tracking, AI/ML Engineer positions make up 76% of the market. At Ahtna, Incorporated, 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 in Demand for This Role
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 $212,000 based on 11,857 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $193,200.
Across all AI roles, the market median is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. For comparison, the highest-paying categories include AI Safety ($253,100) and Research Engineer ($252,000). By seniority level: Entry: $110,408; Mid: $193,200; Senior: $228,700; Director: $272,275; VP: $235,000.
Ahtna, Incorporated AI Hiring
Ahtna, Incorporated has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Anchorage, AK, US.
Location Context
Across all AI roles, 6% (568 positions) offer remote work, while 9,010 require on-site attendance. Top AI hiring metros: New York (2,878 roles, $221,000 median); San Francisco (2,413 roles, $264,500 median); Los Angeles (1,340 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 9,653 open positions tracked in our dataset. By seniority: 193 entry-level, 4,500 mid-level, 3,455 senior, and 1,505 leadership roles (Director, VP, C-Level). Remote roles make up 6% of the market (568 positions). The remaining 9,010 roles require on-site or hybrid attendance.
The market median for AI roles is $213,400. Top-quartile compensation starts at $264,230. The 90th percentile reaches $319,400. Highest-paying categories: AI Safety ($253,100 median, 57 roles); Research Engineer ($252,000 median, 419 roles); AI Engineering Manager ($251,622 median, 51 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 9,653 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (7,301), Data Scientist (441), AI Software Engineer (438). 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 (193) are outnumbered by mid-level (4,500) and senior (3,455) 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 1,505 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 6% of all AI roles (568 positions), with 9,010 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 $213,400. Top-quartile roles start at $264,230, and the 90th percentile reaches $319,400. 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 $253,100 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 (1,605 postings), Aws (916 postings), Azure (724 postings), Rag (634 postings), Gcp (522 postings), Pytorch (495 postings), Kubernetes (384 postings), Claude (383 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
Get Weekly AI Career Intelligence
Salary data, skills demand, and market signals from 16,000+ AI job postings. Every Monday.