AI Research Engineer (Model Compression & Quantization) - 100% Remote Worldwide

Tether Operations Limited

WorldwideremotePosted 16 days ago

Skill Required

AI-Research-and-EngineeringModel-CompressionQuantization-EngineeringInference-OptimizationMachine-Learning-EngineeringRemote-Senior-AI-EngineerAI-ML-Research-EngineerAI-Research-EngineerML-AI-Research-EngineerResearch-EngineerAI EngineerAIMachine Learningrelated fieldEngineeringBlockchainObservabilityData StructuresdesigningbuildingfintechdesignDesign PatternsRustNLPandFulltime

Key highlights

Remote work from anywhere in the world
PhD in NLP, Machine Learning, or related field preferred
Expertise in Metal Shading Language (MSL) and GPU kernels for mobile devices required
Focus on high-performance, low-latency AI model serving and inference optimization

Role overview

Join Tether to pioneer a global financial revolution by empowering businesses to integrate reserve-backed tokens across blockchains, enabling secure, instant, and low-cost digital transactions. As a member of the AI model team, you will drive innovation in model serving and inference architectures, optimizing deployment and inference strategies for high-performance, scalable AI systems across diverse environments, from resource-constrained devices to complex, multi-modal architectures. Your work will focus on delivering high-throughput, low-latency, and memory-efficient AI performance in real-world applications.

Responsibilities

Design and deploy state-of-the-art model serving architectures that deliver high throughput and low latency while optimizing memory usage.
Ensure these pipelines run efficiently across diverse environments, including resource-constrained devices and edge platforms.
Establish clear performance targets such as reduced latency, improved token response, and minimized memory footprint.
Build, run, and monitor controlled inference tests in both simulated and live production environments.
Track key performance indicators such as response latency, throughput, memory consumption, and error rates, with special attention to metrics specific to resource-constrained devices.
Document iterative results and compare outcomes against established benchmarks to validate performance across platforms.
Identify and prepare high-quality test datasets and simulation scenarios tailored to real-world deployment challenges, specifically those encountered on low-resource devices.
Set measurable criteria to ensure that these resources effectively evaluate model performance, latency, and memory utilization under various operational conditions.
Analyze computational efficiency and diagnose bottlenecks in the serving pipeline by monitoring both processing and memory metrics.
Address issues such as suboptimal batch processing, network delays, and high memory usage to optimize the serving infrastructure for scalability and reliability on resource-constrained systems.
Work closely with cross-functional teams to integrate optimized serving and inference frameworks into production pipelines designed for edge and on-device applications.
Define clear success metrics such as improved real-world performance, low error rates, robust scalability, optimal memory usage and ensure continuous monitoring and iterative refinements for sustained improvements.

Requirements

A degree in Computer Science or related field.
Ideally PhD in NLP, Machine Learning, or a related field, complemented by a solid track record in AI R&D (with good publications in A* conferences).
Must have knowledge of Metal Shading Language (MSL). You should be comfortable writing custom compute shaders from scratch.
Proven experience in low-level kernel optimizations and inference optimization on mobile devices is essential.
Your contributions should have led to measurable improvements in inference latency, throughput, and memory footprint for domain-specific applications, particularly on resource-constrained devices and edge platforms.
A deep understanding of modern model serving architectures and inference optimization techniques is required.
This includes state-of-the-art methods for achieving low-latency, high-throughput performance, and efficient memory management in diverse, resource-constrained deployment scenarios.
Must have strong expertise in writing GPU kernels for mobile devices (i.e., smartphones) as well as a deep understanding of model serving frameworks and engines.
Practical experience in developing and deploying end-to-end inference pipelines, from optimizing models for efficient serving to integrating these solutions on resource-constrained devices is required.
Demonstrated ability to apply empirical research to overcome challenges in model serving, such as latency optimization, computational bottlenecks, and memory constraints.
You should be proficient in designing robust evaluation frameworks and iterating on optimization strategies to continuously push the boundaries of inference performance and system efficiency.
Distributed Inference Systems: Designing and optimizing high-performance inference engines using techniques like Tensor Parallelism, Pipeline Parallelism, and Expert Parallelism to handle massive models on GPU clusters.
Deep understanding of the math and structure behind Diffusion Models and Vision Transformers
Understanding of Pruning, Quantization, Flash attention, KV Cache, Speculative Decoding (Eagle) etc.
Excellent English communication skills.

Benefits

Global talent powerhouse working remotely from every corner of the world.
Opportunity to collaborate with some of the brightest minds in the fintech space, pushing boundaries and setting new standards.

Additional details

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.
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.
We’ve grown fast, stayed lean, and secured our place as a leader in the industry.
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Originally posted on Himalayas