AI Research Engineer (Model Evaluation)

Tether Operations Limited; São Paulo; Teletrabalho; BRL 80.000 - 120.000; Tempo integral

Resumo da oferta

Join Tether, a leading company in digital finance, as an AI Model Evaluation Specialist. You will develop evaluation frameworks for AI models, ensuring they perform reliably and efficiently in real-world applications. This role offers the chance to work remotely with a talented global team and make a significant impact in the fintech sector.

Qualificações

• PhD preferred with strong publication record.
• Proven experience in evaluating AI models.
• Familiar with performance metrics like latency and throughput.

Responsabilidades

• Develop evaluation frameworks for AI models during all lifecycle stages.
• Create and manage evaluation datasets and benchmarks.
• Collaborate to align evaluation strategies with business goals.

Conhecimentos

Programming skills

Evaluation metrics expertise

Machine Learning knowledge

Formação académica

Degree in Computer Science or related field

PhD in NLP, Machine Learning or similar

Descrição da oferta de emprego

Join Tether and Shape the Future of Digital Finance

At Tether, we’re pioneering a global financial revolution with innovative blockchain solutions that enable seamless, secure, and transparent digital transactions worldwide.

About Tether

Our product suite includes the trusted stablecoin USDT, energy-efficient Bitcoin mining solutions, advanced data sharing applications like KEET, and educational initiatives to empower individuals in the digital economy.

Why Join Us?

Work remotely with a global team of talented professionals dedicated to innovation in fintech. If you have excellent English communication skills and a passion for technology, Tether offers a dynamic environment to grow and make an impact.

About the Job

We are seeking an experienced AI Model Evaluation Specialist to develop and implement rigorous evaluation frameworks across the AI lifecycle, focusing on model responsiveness, efficiency, and reliability in real-world applications. Responsibilities include designing metrics, benchmarking, collaborating with cross-functional teams, and improving evaluation pipelines.

Responsibilities

1. Develop and deploy evaluation frameworks assessing models during pre-training, post-training, and inference, tracking metrics like accuracy, latency, throughput, and memory usage.
2. Create high-quality evaluation datasets and benchmarks to ensure consistent measurement of model robustness and improvements.
3. Collaborate with product, engineering, and data science teams to align evaluation strategies with business goals, presenting insights via dashboards and reports.
4. Analyze evaluation data to identify bottlenecks, optimize model performance, and ensure resource-efficient deployment.
5. Refine evaluation methodologies through empirical research, staying updated on emerging techniques to enhance model reliability and value.

Minimum Qualifications

• Degree in Computer Science or related field; PhD in NLP, Machine Learning, or similar is preferred, with a strong publication record.
• Proven experience in designing and evaluating AI models at multiple lifecycle stages, with expertise in evaluation metrics and frameworks.
• Strong programming skills and experience building scalable evaluation pipelines, familiar with performance metrics like latency, throughput, and memory footprint.
• Ability to conduct iterative experiments, stay abreast of emerging trends, and refine evaluation practices continuously.
• Experience collaborating with cross-functional teams and translating technical insights into actionable recommendations.