AI Research Engineer

About the Role

The role is part of a global team, working remotely from every corner of the world. You will collaborate with cross-functional teams to integrate reinforcement learning agents into production systems, ensuring continuous monitoring and iterative refinements for sustained domain adaptation. The company is committed to providing a dynamic and supportive work environment, where you can grow and develop your skills as a professional.

Tether is a leader in the fintech industry, with a strong focus on innovation and pushing boundaries. The company has grown rapidly, stayed lean, and secured its place as a leader in the industry. As an AI Research Engineer, you will be part of a team that is shaping the future of the industry.

What You Will Do

• 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, and track key performance indicators.
• Build, run, and monitor controlled reinforcement learning experiments, documenting iterative results and comparing outcomes against established benchmarks.
• Identify and curate high-quality simulation environments and training datasets tailored to specific domain challenges.
• Systematically debug and optimize the reinforcement learning pipeline, analyzing computational efficiency and learning performance metrics.
• Address issues such as reward signal noise, exploration strategy, and policy divergence to improve convergence and stability.
• Collaborate with cross-functional teams to integrate reinforcement learning agents into production systems, defining clear success metrics and ensuring continuous monitoring and iterative refinements.
• Develop and maintain specialized simulation environments and training datasets, ensuring they are tailored to specific domain challenges.
• Work closely with the engineering team to implement and deploy reinforcement learning models in production environments.

What We Are Looking For

• A degree in Computer Science or a related field, with a strong background in machine learning and reinforcement learning.
• Deep expertise in designing reinforcement learning systems and developing novel algorithms.
• Experience with advanced model architectures, including resource-efficient models and complex multi-modal architectures.
• Strong programming skills in languages such as Python and C++.
• Excellent English communication skills, with the ability to collaborate with cross-functional teams.
• Experience working with large datasets and simulation environments.
• Strong analytical and problem-solving skills, with the ability to debug and optimize complex systems.
• Experience with version control systems such as Git.

Nice to Have

• A PhD in NLP, Machine Learning, or a related field.
• Experience working with cloud-based platforms and containerization technologies.
• Familiarity with Agile development methodologies and continuous integration pipelines.
• Experience with data visualization tools and techniques.

Benefits and Perks

• The opportunity to work with a global talent powerhouse, collaborating with like-minded individuals.
• A dynamic and supportive work environment, with opportunities for growth and development.
• Access to cutting-edge technologies and tools, including cloud-based platforms and containerization technologies.
• Flexible working hours and remote work options, allowing you to work from anywhere in the world.
• A competitive compensation package, with benefits and perks tailored to your needs.
• The opportunity to make a significant impact on the company's ability to deliver enhanced intelligence and improved performance.
• Access to a comprehensive training and development program, including workshops and conferences.
• A generous stipend for home office setup and remote work expenses.

• Tip: Showcase your expertise in designing reinforcement learning systems and developing novel algorithms by including examples in your portfolio or resume.
• Be prepared to discuss your experience working with large datasets and simulation environments, and how you have applied these skills in previous roles.
• Highlight your ability to collaborate with cross-functional teams and communicate complex technical concepts to non-technical stakeholders.
• When applying, make sure to tailor your resume and cover letter to the specific requirements of the role, and be prepared to provide examples of your work.
• Research the company and the role beforehand, and be prepared to ask informed questions during the interview process.
• Be prepared to negotiate your salary and benefits package, and have a clear understanding of your worth in the market.
• Red flag: If the company is not transparent about the role or the company culture, or if they are not willing to provide feedback or support during the application process.