AI Research Engineer (Multi-Modal & Vision)
Tether Operations Limited4 months ago
Remote, WorldwideSenior
Responsibilities
- Conduct end-to-end research and engineering on vision-language models across training, evaluation, and optimization.
- Design and implement post-training pipelines using supervised fine-tuning, knowledge distillation, and reinforcement learning from human feedback.
- Curate, filter, balance, and maintain multimodal datasets for domain-specific tasks.
- Adapt and optimize models for resource-constrained environments and real-world deployment at scale.
- Build evaluation frameworks and benchmarks for model performance, robustness, and task success.
- Build and scale training workflows across distributed GPU infrastructure and resolve pipeline bottlenecks.
- Contribute to open-source multimodal AI models, datasets, and tooling.
- Translate current multimodal learning research into practical model improvements and publish findings where applicable.
Requirements
- Degree in Computer Science, Machine Learning, or a related field; an MS or PhD is preferred.
- Strong experience with multimodal post-training workflows, including supervised fine-tuning, knowledge distillation, and reinforcement learning from feedback.
- Hands-on experience with parameter-efficient fine-tuning and distributed training frameworks.
- Demonstrated ability to build and improve vision-language models with measurable benchmark or real-world results.
- Experience adapting models for resource-constrained environments.
- Proven open-source contributions in multimodal AI on GitHub or Hugging Face.
- Publications at leading AI conferences such as NeurIPS, ICML, ICLR, CVPR, or ECCV.
Benefits
- Remote work with a globally distributed team.
- Opportunity to work in a small, high-caliber team on multimodal AI research and production deployment.
Categories
AI ResearchML Engineering
About Tether Operations Limited
Tether Operations Limited develops and issues reserve-backed digital tokens used by exchanges, wallets, payment processors, and merchants, most notably the USDT stablecoin available across multiple blockchains. Founded in 2014 and privately held, it earns revenue from token issuance, reserve management, and related services, and has expanded into tokenization, peer-to-peer communications (Keet), and Bitcoin mining. USDT is widely used in crypto trading and cross-border transfers, including in emerging markets.