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About This Role
Description: Foodland Super Market, Ltd., a locally owned and operated company serving Hawai‘i for over 75 years, is seeking a highly skilled and detail\-oriented Senior Accounting Manager to lead the daily operations of our accounting department. This role oversees general ledger management, financial reporting, account reconciliations, process improvement, and team leadership—including oversight of the internal \& offshore Expense Team.
The Senior Accounting Manager will partner closely with cross\-functional teams to ensure the accuracy, integrity, and compliance of financial information while supporting continuous improvement and operational efficiency. This key leadership role requires strong technical accounting expertise, excellent communication, and a collaborative, solutions\-oriented mindset to support Foodland’s financial health and long\-term organizational goals.
Duties, Expectations \& Responsibilities:
- Accounting Operations \& Oversight
o Oversee day\-to\-day accounting activities, including general ledger, prepaids, fixed assets, capital expenditures, inventory, leases, expenses, and intercompany transactions.
o Manage the quarterly close process, ensuring all journal entries are prepared, posted, and approved accurately and timely.
o Maintain the Sage Fixed Assets system and reconcile activity with Microsoft Dynamics GP to ensure accurate asset tracking.
- Financial Close, Reconciliations \& Reporting
o Ensure timely and accurate reporting of financial information
o Lead quarterly general ledger reconciliations, review accounts, identify and explain variances, and resolve discrepancies.
o Prepare schedules and documentation for annual audits and tax filings, coordinate directly with external auditors and the tax team.
o Maintain annual budgets in the accounting system and support fiscal year\-end closing activities.
- Team Leadership \& Development
o Recruit, lead, monitor, and develop the Accounting Team—including the internal \& offshore Expense Team —through coaching, training, and performance management.
o Set clear expectations and standards for accuracy, timeliness, and operational excellence, including semi\-annual performance evaluations of team.
o Foster a collaborative, accountable, and continuous\-improvement culture.
o Evaluate and improve accounting policies, procedures, and internal controls to enhance accuracy and efficiency.
o Document and update workflow processes and implement system improvements or automation where appropriate.
o Ensure full compliance with GAAP, regulatory requirements, and company policies.
- Collaboration \& Communication
o Partner with management and operational teams to support financial reporting, approvals, and ad hoc analysis.
o Provide timely and clear financial insights to help guide business decisions.
o Communicate expectations, deadlines, and changes to accounting processes across departments.
- Additional Responsibilities
o Perform additional accounting duties, projects, and initiatives assigned to support organizational goals.
Requirements:
o Education: Bachelor’s degree in Accounting, Finance, or related field (CPA preferred but not required, public accounting experience is a plus).
- Experience:
o Minimum 10 years of accounting experience, including at least 5 years in a supervisory or management role in a dynamic and high\-volume environment.
o Oversight of a minimum of $10 million in capital projects and gross revenues of $100 million
o Strong understanding of US GAAP, internal controls, and financial reporting.
o Experience utilizing Sage, Great Plains (Microsoft Dynamics GP), and Microsoft Office Suite.
- Skills \& Competencies:
o Strong analytical skills with the ability to interpret financial data and drive process improvements.
o Excellent communication, organizational, and leadership skills.
o Ability to manage multiple priorities under tight deadlines.
o Experience mentoring, coaching, and developing accounting teams.
o High attention to detail and commitment to accuracy and compliance.
- Work Environment:
o Hybrid (office and remote, based on company schedule).
o Extended hours may be required during quarter\-end, fiscal year\-end, and audit periods.
o Fast\-paced environment requiring multitasking and deadline management.
o Occasional lifting/pushing/pulling of up to 20 lbs.
Benefits:
- 401(k)
- Health, Dental, and Vision Insurance
- Life Insurance
- Flexible Spending Account
- Employee Assistance Program
- Paid Time Off
- Referral Program
Foodland Super Market, Ltd. is an equal opportunity employer committed to diversity, inclusion, and fostering a positive and respectful workplace for all.
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 Foodland Super Market Ltd., 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. Senior-level AI roles across all categories have a median of $227,400.
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.
Foodland Super Market Ltd. AI Hiring
Foodland Super Market Ltd. has 5 open AI roles right now. They're hiring across AI/ML Engineer. Based in Honolulu, HI, US. Compensation range: $120K - $120K.
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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