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DESCRIPTION
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Come build the future of entertainment with us!
Are you interested in shaping the future of movies and television? Do you want to define the next generation of how and what Amazon customers are watching?
Prime Video is a first\-stop entertainment destination offering customers a vast collection of premium programming in one app available across thousands of devices. On Prime Video, customers can customize their viewing experience and find their favorite movies, series, and live events – including Amazon MGM Studios\-produced series and movies Fallout, Heads of State, Reacher, Red One, Road House, The Accountant 2, Beast Games, The Boys, The Lord of the Rings: The Rings of Power, and The Summer I Turned Pretty; licensed fan favorites; Prime member exclusive access to coverage of live sports including Thursday Night Football, NBA, WNBA, NASCAR, NWSL, and The Masters Tournament, and acclaimed sports documentaries including Bye Bye Barry, Kelce, and Earnhardt. Prime Video is one of many benefits of Prime, which bundles savings, convenience, and entertainment into a single membership. Prime members in the U.S. can share a broad range of benefits, including Prime Video, with Amazon Family. All customers, regardless of whether they have a Prime membership or not can access programming via Prime Video subscriptions such as MGM\+, Apple TV, HBO Max, Peacock Premium Plus, FOX One, and Crunchyroll, as well as more than 900 free ad\-supported (FAST) Channels, rent or buy titles, and enjoy even more content for free with ads. Customers can also go behind the scenes of their favorite movies and series with exclusive X\-Ray access, and watch and shop their favorite titles with the fan\-fueled shopping experience Shop the Show in the U.S. For more info visit www.amazon.com/primevideo.
About the Role
The Prime Video Localization Enablement \& Accessibility Program (LEAP) team is seeking a Creative Mixing Lead to support our AI\-assisted dubbing efforts. In this role, you will bring craft\-level expertise in audio post\-production and mixing to the final stages of dubbed title delivery, ensuring AI\-assisted solutions preserve what matters most: sonic fidelity, spatial coherence, dialogue intelligibility, and the artistic intent of the original mix. Working with autonomy while aligning on strategic priorities, you will draw on existing tools and audience insights to guide mixing decisions and uphold audio quality standards across the LEAP dubbing portfolio. You will also partner with diverse creative disciplines, AI engineers, and localization specialists to help develop mixing solutions that serve the team's broader creative strategy.
Key job responsibilities
Lead Creative Decisions for Dubbed Audio Mixes: Ensure creative quality of AI\-assisted mixing operations — evaluating dialogue\-to\-music\-to\-effects (DME) balance, spatial placement, loudness compliance, and tonal consistency. Approve final mixes, stem configurations, and deliverable masters. Interpret quality data and audience research to make tactical creative decisions around dialogue processing, reverb matching, dynamic range, and format\-specific optimization on a per\-title basis.
Collaborate Across Diverse Creative Disciplines: Partner daily with AI engineers, Dubbing Creative Leads, voice synthesis specialists, and quality teams. Prioritize title\-level decisions and direct the creative output of internal mix operators and external partners to maintain sonic consistency.
Contribute to Quality Standards \& Process Improvement: Help ensure AI\-assisted mixing meets Prime Video's customer quality benchmarks through structured testing and feedback loops at several stages. Contribute to the development of internal Standard Operating Procedures (SOPs) that streamline mixing delivery and quality review workflows. Identify opportunities for repeatable mechanisms that improve efficiency and consistency.
Influence Across Teams \& External Partners: Partner with product, engineering, and science teams to align mixing execution with viewer experience goals across playback environments. Contribute to presentations and may deliver content to external stakeholders. May guide break\-out groups in brainstorm sessions, gathering inputs and aligning on creative outputs. Begin to mentor junior mixing team members, and support hiring, onboarding, and training of new team members.
Champion Responsible AI in Creative Contexts: Promote the responsible use of AI technology in audio post\-production to make content more accessible for global audiences while preserving the artistic integrity of the original sound design. At Prime Video and Amazon MGM Studios, our approach to the implementation of generative AI is human\-centered. We believe AI is an impactful tool that augments human creativity, never replacing it.
BASIC QUALIFICATIONS
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- Knowledge of ProTools or other audio or video editing software
- 5\+ years of relevant experience in audio mixing, re\-recording, or audio post\-production.
\- Deep knowledge of professional audio delivery standards — loudness (e.g., \-24 LKFS), dialogue intelligibility, frequency balance, spatial accuracy, and format compliance (Stereo, 5\.1, Atmos).
- Experience leading projects, workstreams, or small teams.
- Bachelor's degree in Audio Engineering, Sound Design, Film Production, or equivalent experience.
- Portfolio demonstrating functional understanding of dialogue mixing, DME stem workflows, and broadcast/streaming delivery standards.
- Fluent in English with demonstrated production or localization mixing experience; proficiency in Latin American Spanish (ES\-419\) is a plus.
PREFERRED QUALIFICATIONS
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- Experience collaborating with cross\-functional teams (product, engineering, localization) to develop insights that drive creative audio executions.
- Demonstrated ability to establish and maintain audio quality standards across large volumes of content.
- Knowledge of AI/ML media tools, voice synthesis technologies, or dubbing production workflows.
- Experience contributing to presentations and delivering content to stakeholders
- Experience managing multiple audio post\-production projects and meeting aggressive deadlines.
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 \- 120,500\.00 \- 163,000\.00 USD annually
Salary Context
This $120K-$163K range is below the median for AI/ML Engineer roles in our dataset (median: $180K across 1937 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 3,823 AI roles we're tracking, AI/ML Engineer positions make up 69% 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 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 $181,170 based on 12,692 positions with disclosed compensation. Senior-level AI roles across all categories have a median of $227,400. This role's midpoint ($141K) sits 22% below the category median. Disclosed range: $120K to $163K.
Across all AI roles, the market median is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($275,000) and AI Safety ($274,200). By seniority level: Entry: $97,880; Mid: $165,000; Senior: $227,400; Director: $247,800; VP: $250,000.
Amazon.com AI Hiring
Amazon.com has 102 open AI roles right now. They're hiring across Research Scientist, AI/ML Engineer, AI Product Manager, Data Scientist. Positions span New York, NY, US, Palo Alto, CA, US, Bellevue, WA, US. Compensation range: $129K - $300K.
Location Context
Across all AI roles, 15% (590 positions) offer remote work, while 3,217 require on-site attendance. Top AI hiring metros: New York (2,643 roles, $211,000 median); San Francisco (2,168 roles, $253,000 median); Los Angeles (1,792 roles, $191,580 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 3,823 open positions tracked in our dataset. By seniority: 112 entry-level, 1,798 mid-level, 1,516 senior, and 397 leadership roles (Director, VP, C-Level). Remote roles make up 15% of the market (590 positions). The remaining 3,217 roles require on-site or hybrid attendance.
The market median for AI roles is $200,100. Top-quartile compensation starts at $253,500. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($275,000 median, 41 roles); AI Safety ($274,200 median, 55 roles); Research Engineer ($260,000 median, 434 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 3,823 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,629), Data Scientist (322), AI Software Engineer (279). 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 (112) are outnumbered by mid-level (1,798) and senior (1,516) 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 397 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 15% of all AI roles (590 positions), with 3,217 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 $200,100. Top-quartile roles start at $253,500, and the 90th percentile reaches $307,500. 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 $275,000 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 (1,979 postings), Aws (1,190 postings), Azure (899 postings), Rag (839 postings), Gcp (726 postings), Pytorch (595 postings), Prompt Engineering (595 postings), Claude (540 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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