Description review

AI Inference Engineer QVAC (100% remote Worldwide)

Tether Operations Limited · Remote · back to the listing

HR standards

60/100

needs work

Title ↔ description

56/100

needs work

Reads as

Machine Learning Engineer

92% confident

What this role officially is

data scientist — ESCO, the EU occupation classification

Data scientists find and interpret rich data sources, manage large amounts of data, merge data sources, ensure consistency of data-sets, and create visualisations to aid in understanding data. They build mathematical models using data, present and communicate data insights and findings to specialists and scientists in their team and if required, to a non-expert audience, and recommend ways to apply the data.

Also known as: data scientists, data engineer, research data scientist, data expert, data research scientist

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What the listing never says

  • No pay range published. Candidates cannot tell whether applying is worth their time. Pay transparency

The listing, marked up

Nothing in the wording of this listing tripped a check. The scores above still judge how complete and coherent it is.

Join Tether and Shape the Future of Digital Finance

At Tether, we’re not just building products, we’re pioneering a global financial revolution. Our cutting-edge solutions empower businesses—from exchanges and wallets to payment processors and ATMs—to seamlessly integrate reserve-backed tokens across blockchains. By harnessing the power of blockchain technology, Tether enables you to store, send, and receive digital tokens instantly, securely, and globally, all at a fraction of the cost. Transparency is the bedrock of everything we do, ensuring trust in every transaction.

Innovate with Tether

Tether Finance: Our innovative product suite features the world’s most trusted stablecoin, USDT, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.

But that’s just the beginning:

Tether Power: Driving sustainable growth, our energy solutions optimize excess power for Bitcoin mining using eco-friendly practices in state-of-the-art, geo-diverse facilities.

Tether Data: Fueling breakthroughs in AI and peer-to-peer technology, we reduce infrastructure costs and enhance global communications with cutting-edge solutions like KEET, our flagship app that redefines secure and private data sharing.

Tether Education: Democratizing access to top-tier digital learning, we empower individuals to thrive in the digital and gig economies, driving global growth and opportunity.

Tether Evolution: At the intersection of technology and human potential, we are pushing the boundaries of what is possible, crafting a future where innovation and human capabilities merge in powerful, unprecedented ways.

Why Join Us?

Our team is a global talent powerhouse, working remotely from every corner of the world. If you’re passionate about making a mark in the fintech space, this is your opportunity to collaborate with some of the brightest minds, pushing boundaries and setting new standards. We’ve grown fast, stayed lean, and secured our place as a leader in the industry.

If you have excellent English communication skills and are ready to contribute to the most innovative platform on the planet, Tether is the place for you.

Are you ready to be part of the future?

About the role:

You will own the inference backbone behind QVAC's local AI stack: the C++ systems layer that makes models run fast, reliably, and predictably on real user hardware. The role is centered on engineering quality at runtime level, including startup behavior, memory pressure, throughput/latency balance, and long-session stability. You will define and evolve the core abstractions that inference features depend on, so new capabilities can be added without sacrificing performance or maintainability. This is a role for someone who enjoys low-level problem solving, clear technical ownership, and building infrastructure that other teams trust in production. Your work directly enables private, on-device AI experiences and helps set the technical foundation for QVAC's next generation of peer-to-peer AI products.

About the job

You'll work on the C++ layer that powers local AI, porting and enhancing inference engines like llama.cpp or similar, to run efficiently on edge devices. Your focus is on the runtime: making models load faster, run leaner, and perform well across different hardware. You'll ensure that the inference layer is stable, optimized, and ready for integration with the rest of the stack.

This role is for engineers who want to work close to the metal, enabling private and fast on-device AI without relying on cloud infrastructure.

Responsibilities

• Work on deploying machine learning models to edge devices using the frameworks: llama.cpp, ggml

• Collaborate closely with researchers to assist in coding, training and transitioning models from research to production environments

• Integrate AI features into existing products, enriching them with the latest advancements in machine learning

Requirements

• Excellent programming skills in C++, experience in Javascript is a bonus

• Strong experience with Llama.cpp and ggml inference engines, which facilitates the deployment of models to specific GPU architectures

• Good understanding of deep learning concepts and model architectures

• Experience with transformers, LLMs, Diffusion models

• Demonstrated ability to rapidly assimilate new technologies and techniques

• A degree in Computer Science, AI, Machine Learning, or a related field, complemented by a solid track record in AI R&D

Important information for candidates
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:

• Apply only through our official channels. We do not use third-party platforms or agencies for recruitment unless clearly stated. All open roles are listed on our official careers page:

• Verify the recruiter’s identity. All our recruiters have verified LinkedIn profiles. If you’re unsure, you can confirm their identity by checking their profile or contacting us through our website.

• Be cautious of unusual communication methods. We do not conduct interviews over WhatsApp, Telegram, or SMS. All communication is done through official company emails and platforms.

• Double-check email addresses. All communication from us will come from emails ending in @ or @

• We will never request payment or financial details. If someone asks for personal financial information or payment at any point during the hiring process, it is a scam. Please report it immediately.

When in doubt, feel free to reach out through our official website.

Highlights

Originally posted on Himalayas

How this was produced

Highlights are found by rule, not by a model: each one is a phrase matched at a known position, and every note is a template we wrote. The two scores come from a typed-decision model (Jev) that reads the listing against the official role definition and real listings for the same role, and returns probabilities rather than prose — it never writes any of the words on this page, and never chooses what to highlight.

Deterministic penalty applied to the HR score: 4 points (from 64 before penalties). Reviewed 21 Sep 2026.