AI Research Engineer (Kernel & Inference Optimization) 100% Remote WorldwideJoin Tether and Shape the Future of Digital FinanceAt 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 TetherTether 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 integral 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 jobAs a member of our AI model team, you will drive innovation in model serving and inference architectures for advanced AI systems.
Your work will focus on optimizing model deployment and inference strategies to deliver highly responsive, efficient, and scalable performance across real‐world applications.
You will work on a wide spectrum of systems,



ranging from resource‐efficient models designed for limited hardware environments to complex, multi‐modal architectures that integrate data such as text, images, and audio.We expect you to have deep expertise in designing and optimizing model serving pipelines and inference frameworks as well as a strong background in advanced model architectures.
You will adopt a hands‐on, research‐drive looking for a Senior Data Scientist Lead to join one of our international clients and lead the design, development, and delivery of data science solutions that generate measurable business value.
This is a high-impact technical leadership role for an experienced Data Scientist who combines strong hands‐on expertise with the ability to guide technical decisions, mentor other data professionals, and collaborate with business and engineering stakeholders.
You will work across the full data science lifecycle, from understanding business problems and defining analytical approaches to developing machine learning models, deploying solutions to production, and continuously improving their performance.
The ideal candidate is highly analytical, hands‐on, business-oriented, and comfortable working with cloud-based data and machine learning environments, particularly AWS .
What To Expect In This Role (Responsibilities)
Data Science Leadership: Lead the design and implementation of data science initiatives, defining methodologies, technical approaches, and best practices across projects.
Machine Learning & Modeling: Develop, evaluate, and optimize statistical and machine learning models to solve complex business problems and generate actionable insights.
End-to-End Data Science: Own the complete data science lifecycle, including data exploration, feature engineering, model development, validation, deployment, monitoring, and continuous improvement.
AWS & Cloud Solutions: Design and implement scalable data science and machine learning solutions leveraging AWS cloud services and best practices.
Technical Leadership: Provide technical guidance to Data Scientists and other technical team members, promoting high‐quality engineering and analytical practices.
Business Collaboration: Work closely with business stakeholders, product teams, data engineers,



and software engineers to translate business challenges into effective data‐driven solutions.
Model Performance & Optimization: Monitor model performance, identify opportunities for improvement, and ensure solutions remain accurate, scalable, and aligned with business objectives.
Data Strategy: Contribute to the definition of data science strategies, analytical frameworks, and best practices that support long-term business growth.
Knowledge Sharing: Mentor team members, conduct technical reviews, and promote knowledge sharing across the organization.
Requirements
Experience: 6+ years of professional experience in Data Science, Machine Learning, Advanced Analytics, or a related field, with proven experience leading technical initiatives or teams.
Data Science Expertise: Strong hands‐on experience with statistical modeling, machine learning algorithms, predictive analytics, experimentation, and data‐driven problem solving.
Programming: Advanced proficiency in Python , with experience using common data science and machine learning libraries such as Pandas, NumPy, Scikit-learn, or similar.
Machine Learning: Strong understanding of supervised and unsupervised learning, model evaluation, feature engineering, optimization, and production machine learning practices.
AWS: Solid hands‐on experience designing or implementing data science and machine learning solutions in AWS environments.
Data & SQL: Strong SQL skills and experience working with large datasets, data warehouses, and complex data environments.
Technical Leadership: Proven ability to lead technical discussions, make architecture and modeling decisions, mentor other professionals, and drive projects from concept to production.
Communication: Advanced English proficiency, with the ability to communicate complex technical concepts clearly with international teams, stakeholders, and leadership.
Problem Solving: Strong analytical and critical‐thinking skills, with a pragmatic approach to solving complex business and technical challenges.
Nice to Have
Experience with AWS services such as SageMaker, S3, Glue, Redshift, Lambda, EMR, or Athena .
Experience deploying and monitoring machine learning models in production.
Expere 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 TransformersUnderstanding of Pruning, Quantization, Flash attention, KV Cache, Speculative Decoding (Eagle) etc.
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