AI Research Engineer (Agentic Post-training) - 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 economiesons.
LangChain.
LangGraph.
AWS.
ML / AI Engineer Senior Remoto Argentina, ID #*****
Toolkits RAG: LangChain Retrievers, LlamaIndex integrations.
Entorno Cloud & Serverless GenAI
Cloud AI Engineer, Google Cloud (English) Share Cloud AI Engineer, Google Cloud (English)
_corporate_fare_ Google _place_ Mexico City, CDMX, Mexico; Buenos Aires, Argentina
**Early**
Experience completing work as directed, and collaborating with teammates; developing knowledge of relevant concepts and processes.
Share Cloud AI Engineer, Google Cloud (English)
_info_outline_
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In most instances,



this position requires in-person interviews as part of the hiring process.
**Minimum qualifications:
Bachelor's degree in Computer Science or equivalent practical experience.
Experience building machine learning solutions and working with technical customers.
Experience designing cloud enterprise solutions and supporting customer projects to completion.
Experience building and deploying custom ML models into production, including experience with deep learning frameworks and with designing and deploying agentic AI workflows for business process automation.
Experience coding in Python, including data structures, algorithms, and software design.
Ability to communicate in English fluently as this is a customer-facing role.
**Preferred qualifications:
Experience with recommendation engines, data pipelines, distributed machine learning, and deep learning frameworks.
Experience in data analytics, data visualization techniques, and core Data Science methodologies.
Experience in software development, professional services, or technical consulting for new technology initiatives.
Knowledge of data warehousing (ETL/ELT), technical architectures, and big data environments (e.g., Hadoop, Spark).
Knowledge of cloud computing, including virtualization, multi-tenant infrastructures, and storage systems.
Excellent customer-facing communication and listening skills with expertise in architecting solutions.
**About the job
The Google Cloud Consulting Professional Services team guides customers through the moments that matter most in their cloud journey to help businesses thrive.
We help customers transform and evolve their business through the use of Google's global network, web-scale data centers,



and software infrastructure.
As part of an innovative team in this rapidly growing business, you will help shape the future of businesses of all sizes and use technology to connect with customers, employees, and partners.
As a Cloud AI Engineer, you will design and implement machine learning solutions for customer use cases, leveraging core Google products including TensorFlow, DataFlow, and Vertex AI.
You will work with customers to identify opportunities to apply machine learning in their business, and travel to customer sites to deploy solutions and deliver workshops to educate and empower customers.
Additionally, you will work closely with Product Management and Product Engineering to build and constantly drive excellence in our products.
In this role, you will work with key Google Cloud customers.
Together with the team, you will support customer implementation of Google Cloud products through: architecture guidance, best practices, data migration, capacity planning, implementation, troubleshooting, monitoring, and much more.
Google Cloud accelerates every organization's ability to digitally transform its business and industry.
We deliver enterprise-grade solutions that leverage Google's cutting-edge technology, and tools that help developers build more sustainably.
Customers in more than 200 countries and territories turn to Google Cloud as their trusted partner to enable growth and solve their most critical business problems.
**Responsibilities
Be a trusted technical advisor to customers and solve complex machine learning challenges.
Coach customers on the practical challenges in machine learning systems: feature extraction and feature definition, data validation, monitoring, and management of features and models.
Work with Customers, Partners, and Google Product teade, datasets, or models) on platforms such as GitHub or Hugging Face.Publications at leading AI conferences (e.g., NeurIPS, ICML, ICLR, ACL, CVPR, ECCV).
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