Interested in this AI/ML Engineer role at Haidilao Hot Pot?
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About This Role
Benefits:
- Provides employees discounts to dine at all 1500\+ Haidilao Hot Pot locations globally
- Provides on\-site staff meal
- Provides medical insurance to qualified full\-time employees
- Provides 401k match to qualified employees
- Provides Birthday gift and celebration
The manager trainee position is expected to be a long\-term transitional role that provides both work assignments and training opportunities to be promoted into store management positions. A trainee will be required to be cross\-trained in all crew level job positions and maintain a working knowledge and proficiency in each, sufficient to supervise the execution of these positions.
Required Skills \& Abilities:
- Preferably Junior Executive specialized in Food/Beverage/Restaurant Service or equivalent;
- Candidates who master more than one language will be added advantage, as oversea assignment will be assigned;
- Hardworking, professional dedication, strong interpersonal communication skills, and strong teamwork spirit
- Obtain the California Food Handler Certificate
Physical Requirements:
- Ability to lift, carry, deliver and/or serve items weighing up to 20\-40 pounds throughout an eight\-hour shift
- Ability to balance serving tray when transferring for food order
- Ability to stand and walk continually throughout an 6\-8 hour shift
- Ability to bend, stoop and reach for products and items
- Ability to work to various temperature environment, for example low temperature in the refrigerator and high temperature in the cooking area
- Ability to clean and maintain station in practicing good safety and sanitation
Education \& Qualifications:
- Candidate must possess at least Bachelor's Degree in any field;
- Applicants with relevant working experience in the related field will be advantage, however applicants without relevant working experience also welcome to apply as full training will be provided;
- California Food Handler Certificate
- Fluent in English / Preferred languages: Mandarin and Spanish
Duties \& Responsibilities:
- Receive training and perform duties in various sections of company’s operations such as Service Department, Kitchen Department, Supporting Function Department etc;
- Gain deep and thorough knowledge of the company’s restaurant operation by rotating on each position;
- Learn from experienced employees to acquire information about methods, procedures, and standards required to perform and excel in your training;
- Progressively master the skills to run restaurant operations.
- Acknowledge and achieve performance goals and objectives defined by management.
- Consistently monitor individual performance and progression with your superior and management.
- Upon completion of all basic training, set new goals and objectives with the management for your progression in the company.
- Provide support as needed in various departments;
- Perform ad\-hoc duties as assigned by your superior.
- Performs other related duties as assigned.
Founded in 1994, Haidilao has become an internationally renowned hotpot brand and catering giant with over 20 years' development.
By the end of June 30, 2020, Haidilao had opened 935 chain restaurants in China, Singapore, the U.S., South Korea, Japan, Canada, the United Kingdom, Malaysia, Vietnam, Indonesia, and Australia.
Over the years, Haidilao has withstood the challenges of the market as well as customers, and has successfully forged a quality hot pot brand that has earned a reputation for itself. Haidilao combines kinds of characteristics of hot pot in many places of China. As a large\-scale chain catering enterprise with operations all over the world, Haidilao adheres to integrity in business. It gives the highest priority to continuously improving the quality and safety of its food products, providing more thoughtful services to its customers while delivering healthier, safer and more nutritious food.
Pay: $18\.00 \- $25\.00 / hour
Job Type: fulltime, parttime
Education: No education required
Work location: On\-site
Salary Context
This $37K-$52K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $100K across 15465 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 10,872 AI roles we're tracking, AI/ML Engineer positions make up 91% of the market. At Haidilao Hot Pot, 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 ($44K) sits 71% below the category median. Disclosed range: $37K to $52K.
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.
Haidilao Hot Pot AI Hiring
Haidilao Hot Pot has 1 open AI role right now. They're hiring across AI/ML Engineer. Based in Queens, NY, US. Compensation range: $52K - $52K.
Location Context
Across all AI roles, 11% (1,212 positions) offer remote work, while 9,626 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 10,872 open positions tracked in our dataset. By seniority: 871 entry-level, 6,773 mid-level, 2,013 senior, and 1,215 leadership roles (Director, VP, C-Level). Remote roles make up 11% of the market (1,212 positions). The remaining 9,626 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 10,872 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (9,872), AI Software Engineer (262), Data Scientist (256). 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 (871) are outnumbered by mid-level (6,773) and senior (2,013) 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 1,215 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 11% of all AI roles (1,212 positions), with 9,626 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: Python (1,782 postings), Aws (1,065 postings), Azure (796 postings), Rag (710 postings), Gcp (617 postings), Pytorch (602 postings), Prompt Engineering (516 postings), Tensorflow (511 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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