AI Research Engineer (Multi-Modal Reinforcement Learning) - 100% Remote Worldwide
Tether Operations Limited5 months ago
Remote, WorldwideSenior
Responsibilities
- Research reinforcement learning algorithms for diffusion-based, autoregressive, and unified multimodal models.
- Design and build scalable, distributed reinforcement learning infrastructure for multimodal systems.
- Develop reward modeling strategies to improve training stability, align behavior, and mitigate reward hacking.
- Create and curate multimodal simulation environments and training datasets.
- Design benchmarking and evaluation protocols for multimodal reinforcement learning systems.
- Analyze policy bottlenecks involving training, credit assignment, cross-modal alignment, and reward optimization.
- Investigate next-generation reinforcement learning paradigms that learn from environment feedback.
- Publish research findings in top-tier conferences including ICML, NeurIPS, ICLR, CVPR, ICCV, and ECCV.
Requirements
- A Master's degree in Computer Science or a related field is required; a PhD in Machine Learning, NLP, Computer Vision, or a related discipline is preferred.
- A strong track record of AI research and publications in top-tier conferences is required.
- Proven experience running large-scale reinforcement learning experiments in multimodal and vision-centric systems, including online RL settings.
- Deep understanding of reinforcement learning algorithms and optimization for vision and multimodal learning, including policy stability, exploration, and sample efficiency.
- Strong proficiency in PyTorch and deep learning frameworks for vision and multimodal AI.
- Hands-on experience building end-to-end RL pipelines covering simulation, training, evaluation, and deployment in production-grade systems.
- Experience addressing sample inefficiency, exploration-exploitation tradeoffs, training instability, evaluation design, and algorithmic improvement for multimodal and vision tasks.
Benefits
- 100% remote work worldwide.
- Opportunity to work on innovative AI and reinforcement learning systems within Tether's global fintech and technology organization.
Tech Stack
Categories
AI Research
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.