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The job opportunity is for the role of an AI Research Engineer at Tether, a fast-growing fintech company headquartered in El Salvador, with a global remote team. Tether is looking to fill this full-time position with candidates passionate about contributing to innovative AI solutions. The role enables engineers to work from anywhere in the world, making it an appealing opportunity for those preferring remote work.
The primary responsibilities of the AI Research Engineer include:
Development of Reinforcement Learning Algorithms: Candidates are expected to develop and implement state-of-the-art reinforcement learning algorithms aimed at optimizing decision-making processes in simulated and real-world environments. Establishing performance targets like reward maximization and policy stability is critical.
Experiment Management: Engineers will build, run, and monitor controlled reinforcement learning experiments. They will track performance indicators, document the results, and compare these to established benchmarks.
Data and Environment Curation: Identifying and curating high-quality simulation environments and training datasets tailored to specific domain challenges is crucial. Engineers will set measurable criteria to ensure these resources enhance both learning processes and overall model performance.
Pipeline Optimization: Systematic debugging and optimization of the reinforcement learning pipeline will be part of the role. Analyzing computational efficiency and learning performance metrics, they will address issues related to reward signal noise, exploration strategy, and policy divergence to enhance convergence.
Collaboration with Cross-Functional Teams: Candidates will work alongside various teams to integrate reinforcement learning agents into production systems, ensuring defined success metrics and continuous monitoring for sustained domain adaptation.
To qualify for the AI Research Engineer position, candidates should have:
A degree in Computer Science or a related field, with a preference for a PhD in Natural Language Processing (NLP), Machine Learning, or equivalent experience in AI research and development.
Proven experience conducting large-scale reinforcement learning experiments, particularly using online RL techniques like Group Relative Policy Optimization (GRPO).
A deep understanding of reinforcement learning algorithms, particularly online RL methods, and optimization techniques that enhance policy stability, exploration, and sample efficiency.
Strong proficiency in PyTorch and relevant reinforcement learning frameworks, along with practical experience in developing RL pipelines.
Demonstrated ability to overcome challenges in reinforcement learning, emphasizing the application of empirical research to enhance algorithmic innovations.
While specific skills were not detailed in the job description, the expected competencies are clearly advanced:
Excellent English communication skills are essential, enabling effective collaboration and idea sharing within the team.
Ability to work in a hands-on, research-driven environment, with an emphasis on developing, testing, and implementing novel algorithms.
Tether promotes a dynamic work culture, attracting global talent to collaborate on pushing boundaries in fintech. The company prides itself on being a leader in the industry while maintaining lean operations. If contributing to cutting-edge AI technology excites you, Tether presents an enriching opportunity to be part of the future in fintech.
Tether provides important guidelines for candidates to ensure a safe application experience:
For job seekers, the AI Research Engineer position at Tether offers a unique opportunity to work on innovative AI algorithms in a supportive remote environment. Candidates who possess the requisite qualifications and passion for pioneering solutions in the fintech sector should consider applying. With the potential for highly impactful work and collaborative opportunities with experts in the field, this could be a significant stepping stone in one’s career.
This job offer was originally published on weworkremotely.com
April 3, 2026
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