AI Systems Modeler

2 days ago

Dublin, Dublin City, Ireland beBeeMachine Full time €80,000 - €125,000

Transform the digital finance landscape with innovative solutions. Shape the future by integrating reserve-backed tokens across blockchains:

- Tether Finance: Deliver seamless stablecoin USDT and digital asset tokenization services.

- Tether Power: Provide eco-friendly energy solutions for Bitcoin mining.

- Tether Data: Leverage cutting-edge data sharing and AI solutions like KEET.

- Tether Education: Develop digital learning initiatives for individuals in the gig economy.

- Tether Evolution: Foster technology and human potential innovation hubs.

About the Role

As a model engineer, develop evaluation frameworks and benchmark methodologies for pre-training, post-training, and inference of AI models. Design metrics and assessment strategies to ensure models are responsive, efficient, and reliable across various applications and hardware environments.

Responsibilities
  • Design and deploy evaluation frameworks assessing models at all stages, tracking key performance indicators such as accuracy, latency, throughput, and memory footprint.
  • Create evaluation datasets and benchmarks to measure model robustness and improvements.
  • Collaborate with cross-functional teams to align evaluation metrics with business goals, presenting insights through dashboards and reports.
  • Analyze evaluation data to identify bottlenecks, propose optimizations, and enhance model performance and scalability.
  • Refine evaluation methodologies through experiments and research, staying updated on emerging techniques.

Qualifications
  • Degree in Computer Science or related field; PhD in NLP, Machine Learning, or similar is preferred.
  • Proven experience in designing and evaluating AI models across different lifecycle stages.
  • Strong programming skills and experience with evaluation benchmarks, pipelines, and performance metrics.
  • Ability to conduct iterative experiments and stay current with emerging trends.
  • Experience working with cross-functional teams and translating technical insights into actionable recommendations.

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