reinforcement learning engineer

Tether Operations Limited

<div>Join Tether and Shape the Future of Digital Finance
At Tether, we&rsquo;re not just building products, we&rsquo;re pioneering a global financial revolution. Our cutting-edge solutions empower businesses&mdash;from exchanges and wallets to payment processors and ATMs&mdash;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&rsquo;s most trusted stablecoin, USDT, relied upon by hundreds of millions worldwide, alongside pioneering digital asset tokenization services.
But that&rsquo;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&rsquo;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&rsquo;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 job
As a member of the AI model team, you will drive innovation in reinforcement learning approaches for advanced models. Your work will optimize decision-making and adaptive behavior to deliver enhanced intelligence, improved performance, and domain-specific capabilities for real-world challenges. You will work across a broad spectrum of systems, including resource-efficient models designed for limited hardware environments and complex multi-modal architectures that integrate data such as text, images, and audio.
We expect you to have deep expertise in designing reinforcement learning systems and a strong background in advanced model architectures. You will adopt a hands-on, research-driven approach to developing, testing, and implementing novel reinforcement learning algorithms and training frameworks. Your responsibilities include curating specialized simulation environments and training datasets, strengthening baseline policy performance, and identifying as well as resolving bottlenecks in the reinforcement learning process. The ultimate goal is to unlock superior, domain-adapted AI performance and push the limits of what these models can achieve in dynamic, real-world environments.
Responsibilities<ul><li>
Develop and implement state-of-the-art reinforcement learning algorithms designed to optimize decision-making processes in both simulated and real-world settings. Establish clear performance targets such as reward maximization and policy stability.</li><li>
Build, run, and monitor controlled reinforcement learning experiments. Track key performance indicators while documenting iterative results and comparing outcomes against established benchmarks.</li><li>
Identify and curate high-quality simulation environments and training datasets that are tailored to specific domain challenges. Set measurable criteria to ensure that the selection and preparation of these resources significantly enhance the learning process and overall model performance.</li><li>
Systematically debug and optimize the reinforcement learning pipeline by analyzing both computational efficiency and learning performance metrics. Address issues such as reward signal noise, exploration strategy, and policy divergence to improve convergence and stability.</li><li>
Collaborate with cross-functional teams to integrate reinforcement learning agents into production systems. Define clear success metrics such as real-world performance improvements and robustness under varied conditions and ensure continuous monitoring and iterative refinements for sustained domain adaptation.</li></ul><ul><li>
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&amp;D (with good publications in A* conferences).</li><li>
Proven experience with large-scale reinforcement learning experiments, including online RL techniques such as Group Relative Policy Optimization (GRPO), is essential. Your contributions should have led to measurable improvements in domain-specific decision-making and overall policy performance.</li><li>
Deep understanding of reinforcement learning algorithms is required, including state-of-the-art online RL methods and other gradient-based optimization approaches like policy gradients, actor-critic, and GRPO. Your expertise should emphasize enhancing policy stability, exploration, and sample efficiency in complex, dynamic environments.</li><li>
Strong expertise in PyTorch and relevant reinforcement learning frameworks is a must. Practical experience in developing RL pipelines, from simulation and online training to post-training evaluation and deploying RL-based solutions in production environments is expected.</li><li>
Demonstrated ability to apply empirical research to overcome reinforcement learning challenges such as sample inefficiency, exploration-exploitation tradeoffs, and training instability. You should be proficient in designing robust evaluation frameworks and iterating on algorithmic innovations to continuously push the boundaries of RL agent performance.</li></ul>
Important information for candidates 
Recruitment scams have become increasingly common. To protect yourself, please keep the following in mind when applying for roles:<ul><li>
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: https://tether.recruitee.com/</li><li>
Verify the recruiter&rsquo;s identity. All our recruiters have verified LinkedIn profiles. If you&rsquo;re unsure, you can confirm their identity by checking their profile or contacting us through our website.</li><li>
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.</li><li>
Double-check email addresses. All communication from us will come from emails ending in @tether.to or @tether.io</li><li>
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.</li></ul>
When in doubt, feel free to reach out through our official website.</div>

AI Research Engineer - Reinforcement Learning (100% remote Worldwide)

YO IT CONSULTING

<div>Location: Remote (Work from Anywhere)
Job Type: Contract / Freelance
Job Overview 
We are looking for Image Reinforcement Learning (RL) Experts to work on a cutting-edge AI project focused on improving image-based machine learning systems. The role involves designing tasks, datasets, and evaluation frameworks to enhance AI model reasoning and performance in image-related applications.
This is a remote, project-based opportunity ideal for professionals with strong experience in computer vision, reinforcement learning, and AI model evaluation.
Key Responsibilities 
Develop and implement reinforcement learning approaches for image-based tasks 
Design training datasets and evaluation benchmarks for image AI models 
Analyze and improve model performance in image recognition and visual reasoning 
Work with machine learning pipelines for image classification, detection, and segmentation 
Collaborate with AI researchers to improve model accuracy and decision-making 
Create clear documentation of workflows, datasets, and evaluation methods
Required Qualifications 
Bachelor&rsquo;s or Master&rsquo;s degree in Computer Science, Artificial Intelligence, Machine Learning, or related field 
Strong experience with Reinforcement Learning (RL) 
Hands-on experience with Computer Vision / Image Processing 
Experience with Python and ML frameworks such as: 
PyTorch 
TensorFlow 
OpenCV 
Knowledge of deep learning models for image analysis</div>

Image Reinforcement Learning (RL) Expert – Remote

Video Annotation & OCR Project - Remote

Search 10000+ Reinforcement learning engineer jobs near you this March. New roles added regularly across leading industries. Apply today.

10000 reinforcement learning engineer jobs Near Me

AI Research Engineer - Reinforcement Learning (100% remote Worldwide)

Image Reinforcement Learning (RL) Expert – Remote

Video Annotation & OCR Project - Remote

Image Reinforcement Learning (RL) Expert – Remote

Image Reinforcement Learning (RL) Expert – Remote

Image Reinforcement Learning (RL) Expert – Remote

Video Annotation & OCR Project - Remote