Interested in this AI/ML Engineer role at Amazon.com?
Apply Now →Skills & Technologies
About This Role
DESCRIPTION
---------------
As a Gen AI / VFX Coordinator on our US Series team, you will be partnering with the US Series VFX Executives with a focus on Generative AI workflows \& initiatives. You will assist with enabling productions and will support Executives and productions with navigating the complexities of utilizing Gen AI technology. We are looking for someone who has enough production experience and intuition to see each show as a whole and help to set it up for success; as well as someone who can anticipate how and when to engage actively to keep it on track for success. Your proactive approach will allow you to play a central role in understanding our cross\-functional partners from across the studio and know when to engage. You will be a sounding board as a partner in the GEN AI workflow for the US Series VFX Executives, and provide organizational support with AI vendor evaluations, AI tool evaluations, execution and tracking of AI VFX \& Previz work, and other Gen AI\-related administrative duties to keep our shows on track.
Key job responsibilities
- Manage daily, weekly, monthly schedules for US Series Gen AI \& VFX Executives engaging in GEN AI utilizations and assisting with reporting up to the Director of Visual Effects for US Series.
- Assist Gen AI \& VFX Executives with organizing meetings with external AI companies, tool developers and AI vendors, as well as internal stakeholders.
- Assist with notetaking and keeping VFX\-related AI tool \& vendor records updated in an internal database. Build a robust database referencing global AI vendors, their Gen AI capabilities and studio and show level counterparts with a GEN AI focus.
- Track creative notes, reference material, media files and delivered versions of AI VFX/previz material; assist with preparing before\-\&\-after reels and presentations.
- Maintain a checklist for each show with a GEN AI focus to ensure major milestones and requirements are met (e.g. security approvals, tools approvals, Legal Gen AI use\-case approvals, alignment with key Creative, Production \& VFX stakeholders, etc.)
- Assist in the breakdown of scripted materials to determine scope of visual effects with a GEN AI focus.
- Provide assistance as needed with all aspects of VFX production; from development and pre\-production through final delivery with a GEN AI focus.
- Collaborate with and support efforts to create better alignment between internal departments, Production Executives and Creative Executives with a GEN AI focus.
- Liaise between vendors, crew, and internal teams to improve vertical information flow.
- Track and manage VFX schedules, keeping stakeholders apprised of status with a GEN AI focus.
- Support the US Series VFX Executives in tracking and maintaining VFX script breakdowns, budgets, and weekly progress reporting with a GEN AI focus.
- Facilitate GEN AI VFX reviews with creative teams and relay feedback as needed.
- Assist in the preparation of bid packages for vendor partners as well as general coordination of the bidding process: Creation of Aspera accounts, gathering of all project materials, bid template prep for vendor partners, creation of bid briefs, and other bidding documents as needed with a GEN AI focus.
- Assist in gathering availability information for VFX show side keys (Freelance AI Supervisors, VFX Supervisors/VFX Producers) with a GEN AI focus.
- Prepare agendas and presentations for management meetings with a GEN AI focus; coordinate meeting summaries; ensure distribution to appropriate executives; monitor and/or follow up on items
- Facilitate communication with the show level and studio departments (e.g. casting, business affairs, legal, finance, PR/marketing, etc.)
- Coordinate kick\-off calls with development for each individual project with a GEN AI focus.
- Work with key Gen AI Executives in initiatives such as final pixel VFX, Previz, Concept Art \& Design and complete other Gen AI initiatives \& deep dives per studio requirements.
- Assist and facilitate general requests and communication to ensure shows are following studio guidelines and procedures.
BASIC QUALIFICATIONS
------------------------
- 3\+ years of experience as a VFX Coordinator or on\-set Production Coordinator
- Awareness and understanding of GEN AI tools such as Kling, Seedance, Gemini Flash, GPT Image 2, Comfy UI, Runway, Magnific, etc.
- Understanding of foundational concepts related to Machine Learning and Generative AI.
- Excellent organizational skills, calendar management, meeting scheduling and note\-taking
- Understanding of the Visual Effects process and basic VFX principles, workflow and terminology.
- Knowledge of creative, production, post\-production processes and related workflows with a GEN AI focus.
- Knowledge of digital audio and video file formats.
- Working knowledge of outside VFX and Virtual Production facilities and freelance talent with a GEN AI focus.
- Extremely organized and detail oriented. Perfectionist – loves and lives by process. Excellent time management skills.
- A love of data and efficiency through using technology to solve problems. Familiarity with production and post software such as Shotgrid, Movie Magic Budgeting, FileMaker, PIX, Cinesync, Tableau, RV and newer platforms such as Flow Capture is a plus.
PREFERRED QUALIFICATIONS
----------------------------
- Versed in 3p GEN AI tools
- 5\+ years of VFX experience
- Direct experience creating visual content with GEN AI tools such Kling, Seedance, Gemini Flash, GPT Image 2, ComfyUI, Runway, Magnific, etc.
- Strong interpersonal skills accompanied by a high degree of sensitivity for confidentiality.
- Excellent oral and written communication techniques
- Ability to gather data and return reliable, pertinent information to Executive for action with a GEN AI focus.
- Multi\-task oriented with an excellent sense of priority; logic and objectivity, highly organized and capable of handling a number of sensitive and important issues simultaneously.
\- Anticipatory Planning \& Management \- Acts on behalf of the US Series VFX and Gen AI Executives in areas such as follow\-up, monitoring calendar for conflicts, and communicating requests for information and routing to the appropriate person.
- Even\-tempered, grace under pressure and collaborative problem\-solving abilities.
\- Conceptual/Critical Thinking \- Keeping abreast of the business matters addressed to the US Series VFX and Gen AI Executives and Global Head of Visual Effects, utilizing the appropriate resources to ensure accurate and timely information/data gathering and follow\-up on all issues.
- Willingness to continue learning to ensure understanding of current and future production process with a GEN AI focus.
- Ability to navigate and cross\-communicate effectively within the studio and at show level with a GEN AI focus.
- Passionate about Amazon’s Culture and Leadership Principles in the workplace.
- Meets/exceeds Amazon’s leadership principles requirements for this role
- Meets/exceeds Amazon’s functional/technical depth and complexity for this role
Amazon is an equal opportunity employer and does not discriminate on the basis of protected veteran status, disability, or other legally protected status.
Los Angeles County applicants: Job duties for this position include: work safely and cooperatively with other employees, supervisors, and staff; adhere to standards of excellence despite stressful conditions; communicate effectively and respectfully with employees, supervisors, and staff to ensure exceptional customer service; and follow all federal, state, and local laws and Company policies. Criminal history may have a direct, adverse, and negative relationship with some of the material job duties of this position. These include the duties and responsibilities listed above, as well as the abilities to adhere to company policies, exercise sound judgment, effectively manage stress and work safely and respectfully with others, exhibit trustworthiness and professionalism, and safeguard business operations and the Company’s reputation. Pursuant to the Los Angeles County Fair Chance Ordinance, we will consider for employment qualified applicants with arrest and conviction records.
Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a workplace accommodation or adjustment during the application and hiring process, including support for the interview or onboarding process, please visit https://amazon.jobs/content/en/how\-we\-hire/accommodations for more information. If the country/region you’re applying in isn’t listed, please contact your Recruiting Partner.
The base salary range for this position is listed below. Your Amazon package will include sign\-on payments and restricted stock units (RSUs). Final compensation will be determined based on factors including experience, qualifications, and location. Amazon also offers comprehensive benefits including health insurance (medical, dental, vision, prescription, Basic Life \& AD\&D insurance and option for Supplemental life plans, EAP, Mental Health Support, Medical Advice Line, Flexible Spending Accounts, Adoption and Surrogacy Reimbursement coverage), 401(k) matching, paid time off, and parental leave. Learn more about our benefits at https://amazon.jobs/en/benefits.
USA, CA, Culver City \- 26\.87 \- 47\.06 USD hourly
Salary Context
This $54K-$97K range is in the lower quartile for AI/ML Engineer roles in our dataset (median: $180K across 1841 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 3,708 AI roles we're tracking, AI/ML Engineer positions make up 70% of the market. At Amazon.com, 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 $218,750 based on 3,817 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $200,000. This role's midpoint ($75K) sits 65% below the category median. Disclosed range: $54K to $97K.
Across all AI roles, the market median is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. For comparison, the highest-paying categories include AI Safety ($300,000) and Research Engineer ($280,000). By seniority level: Entry: $120,000; Mid: $200,000; Senior: $230,000; Director: $272,150; VP: $250,000.
Amazon.com AI Hiring
Amazon.com has 97 open AI roles right now. They're hiring across Research Scientist, AI/ML Engineer, Data Scientist, AI Product Manager. Positions span Sunnyvale, CA, US, Culver City, CA, US, San Francisco, CA, US. Compensation range: $97K - $327K.
Location Context
Across all AI roles, 14% (508 positions) offer remote work, while 3,180 require on-site attendance. Top AI hiring metros: New York (1,045 roles, $220,000 median); San Francisco (810 roles, $277,088 median); Los Angeles (397 roles, $215,000 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 3,708 open positions tracked in our dataset. By seniority: 102 entry-level, 1,705 mid-level, 1,469 senior, and 432 leadership roles (Director, VP, C-Level). Remote roles make up 14% of the market (508 positions). The remaining 3,180 roles require on-site or hybrid attendance.
The market median for AI roles is $217,500. Top-quartile compensation starts at $272,100. The 90th percentile reaches $325,000. Highest-paying categories: AI Safety ($300,000 median, 21 roles); Research Engineer ($280,000 median, 147 roles); AI Architect ($254,798 median, 67 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 3,708 open positions across 16 role categories. The largest categories by volume: AI/ML Engineer (2,605), Data Scientist (310), AI Software Engineer (259). 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 (102) are outnumbered by mid-level (1,705) and senior (1,469) 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 432 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 14% of all AI roles (508 positions), with 3,180 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 $217,500. Top-quartile roles start at $272,100, and the 90th percentile reaches $325,000. 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 $300,000 median, while Prompt Engineer roles sit at $140,000. 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 (1,890 postings), Aws (1,103 postings), Azure (877 postings), Rag (855 postings), Gcp (631 postings), Prompt Engineering (560 postings), Pytorch (545 postings), Claude (498 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.