Interested in this AI/ML Engineer role at Lectriverse?
Apply Now →About This Role
If you’re good at making conversation and enjoy talking about a variety of subjects, you’re invited to audition for an AI chatbot voice project \-\- even if you've never done so before.
This job is for fluent Arabic speakers \- GULF, MSA and other dialects. You will work with an Arabic language producer, so you do not have to speak English to qualify.
We are a company specializing in providing voices for major chatbot companies around the world. We're looking for good speakers and you don't have to be a professional to qualify.
The content you record may be used for computer training or for pure entertainment. There are no limits to how many hours of performance you may be hired to do, and yes, this work pays an average of $500 per hr, which entitles our clients to use of your voice recordings for their future products.
PLEASE NOTE: If you have any usage concerns about your voice being used for online entertainment in this way, please do NOT audition.
Still with us? Here are the details:
You'll need to record a 30\-second audition of your voice, details below. If you are chosen, each job will be one of the two possible types:
1\. A 500\-word script that pays $700 for a full buy\-out. This is a 10\-30 minute session you record on your own (full details, script and instruction provided) and then send in. No editing required on your part — we’ll edit for you!
2\. A 60\-minute script @ $500\-800 per hr, with a full buyout for 10,000 words recorded (usually takes 2\-3 hours of booth time, and is produced live with our director in a zoom call). You do the talking, we do all the editing.
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SEND Your mp3 audition to: [email protected] \-\- *more info below*
*PLEASE READ THIS WHOLE TEXT TO KEEP YOUR AUDITION FROM BEING DISQUALIFIED!*
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How to Audition
This is a personality acting job. We're looking for people who can imitate different styles of speaking: narration, deep, rich\-sounding, motivational presenter, gossip\-monger, favorite anime characters, impressions of famous people and actors and the like. Anything that steps you out of your normal voice and into a style others might recognize.
Examples for Women:
Speech\-making politician, bored housewife, sassy teen, egotistical intellectual, rebelious daughter, mother dearest, privileged rich girl, foreign accent tourist, tough company boss, etc.
Examples for Men:
Documentary narrator, deep husky, drill sergeant, elementary school teacher, nerdy office worker, immature, frightened, wily cartoon cat, etc.
These are just suggestions — do your best characters — bright, cheerful, positive, serious storyteller, deep, powerful, intimidating, cute, innocent, warm, charming — the possibilities are endless!
Recording Your Audition, Step\-by\-Step:
1\. Pick three styles of characters, take a moment to practice what they sound like, and then using your phone or external microphone and record about 10\-15 seconds of speaking in that character about any subject you like.
Whatever you choose, pick ways to show the range of your voice, especially your high and low range.
*Do NOT* *identify each character, just switch from one to the next.*
*Do NOT* *add music or sound effects — we want to hear your voice only, avoiding any background noise.*
\[A note to professional actors: You may submit your existing character reel, but please tightly edit to under one minute, and if possible, eliminate any sweetening.]
2\. Record your digital file with three different character examples. When finished, listen back to be sure the recording is clear and that there are no distracting noises in the background.
*3\.* Once you are satisfied with your recording, *EXPORT it as an mp3\.*
4\. LABEL your mp3 audition like this:
AR\_Char\_Your Name.mp3
(AR for Arabic, Char for character, then your first and last name):
*Please DO NOT* *announce your name at the beginning or end of the file* *\- just start talking!*
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4\. SEND your mp3 audition to: [email protected]
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Communication
In general, we will acknowledge your submission but will not otherwise be in touch until one of our clients indicates they want to book you. So *please be patient.* We expect these projects to record through December of this year!
And thanks very much for your interest. We need many voices, so we hope you will take a moment to participate. If you have friends or family members 18 or older, you can invite them to record their own auditions as well!
Pay: $300\.00 \- $600\.00 per hour
People with a criminal record are encouraged to apply
Work Location: Remote
Salary Context
This $624K-$1248K range is above the 75th percentile for AI/ML Engineer roles in our dataset (median: $181K across 1996 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 3,824 AI roles we're tracking, AI/ML Engineer positions make up 71% of the market. At Lectriverse, 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 $178,940 based on 11,900 positions with disclosed compensation. Mid-level AI roles across all categories have a median of $160,000. This role's midpoint ($936K) sits 423% above the category median. Disclosed range: $624K to $1248K.
Across all AI roles, the market median is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. For comparison, the highest-paying categories include AI Engineering Manager ($293,500) and AI Safety ($274,200). By seniority level: Entry: $97,380; Mid: $160,000; Senior: $227,400; Director: $243,000; VP: $250,000.
Lectriverse AI Hiring
Lectriverse has 3 open AI roles right now. They're hiring across AI/ML Engineer. Based in Remote, US. Compensation range: $1248K - $1248K.
Remote Work Context
Remote AI roles pay a median of $169,035 across 1,817 positions. About 16% of all AI roles offer remote work.
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 3,824 open positions tracked in our dataset. By seniority: 119 entry-level, 1,813 mid-level, 1,472 senior, and 420 leadership roles (Director, VP, C-Level). Remote roles make up 16% of the market (613 positions). The remaining 3,187 roles require on-site or hybrid attendance.
The market median for AI roles is $200,000. Top-quartile compensation starts at $253,000. The 90th percentile reaches $307,500. Highest-paying categories: AI Engineering Manager ($293,500 median, 31 roles); AI Safety ($274,200 median, 51 roles); Research Engineer ($260,000 median, 401 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 3,824 open positions across 15 role categories. The largest categories by volume: AI/ML Engineer (2,702), Data Scientist (281), AI Software Engineer (258). 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 (119) are outnumbered by mid-level (1,813) and senior (1,472) 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 420 positions, representing the bottleneck between technical execution and organizational strategy.
Remote work availability sits at 16% of all AI roles (613 positions), with 3,187 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 $200,000. Top-quartile roles start at $253,000, 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 $293,500 median, while Prompt Engineer roles sit at $142,800. 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 (1,968 postings), Aws (1,203 postings), Azure (882 postings), Rag (877 postings), Gcp (735 postings), Prompt Engineering (587 postings), Pytorch (586 postings), Claude (554 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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