AI Research Engineer (Multi-Modal Reinforcement Learning) - 100% Remote Worldwide

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Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Lead research in multi-modal reinforcement learning, designing scalable RL infrastructure for distributed training across modalities, building and curating simulation environments and datasets, and publishing results in top conferences. Drive improvements in reward modeling, policy optimization, and cross-modal alignment while collaborating with a global, remote team.

Location: Rome, Buenos Aires, Bogotá, São Paulo, Montevideo, Bengaluru, Chittagong, Karachi, Tokyo, Hanoi, Taipei, Bangkok, London, Barcelona, Dubai, Sofia, Prague, Belgrade, Copenhagen, Tallinn, Athens, Dublin, Oslo, Amsterdam, Warsaw, Lisbon, Bucharest, Stockholm, Brussels, Tel Aviv, Nicosia

Workplace: Remote

Employment Type: Full time

Job Function: Education & Training

Key Responsibilities

•Conduct research on reinforcement learning algorithms for multimodal models, including diffusion-based approaches for image autoregressive models for multimodal understanding, and unified frameworks that integrate multiple modalities.
•Design and build reinforcement learning infrastructure that supports scalable, distributed training across multimodal systems while maintaining efficiency and reliability.
•Develop and refine reward modeling strategies that improve training stability, align model behavior with desired outcomes, and mitigate reward hacking and related failure modes.
•Create and curate multimodal simulation environments and datasets to support robust training, evaluation, and benchmarking of reinforcement learning systems.
•Design and conduct rigorous benchmarking and evaluation protocols to measure model performance, track progress against baselines, and validate improvements across multimodal tasks.

Key Requirements

•Master's degree in Computer Science or related field; PhD in Machine Learning, NLP, Computer Vision, or closely related discipline preferred, with a strong track record of AI research and publications in top-tier conferences.

Experience:MultimodalReinforcement learningAI research

Education:Bachelor's

Skills:ResearchProblem-solvingCommunication

Languages:English

Tech Stack:PyTorchDiffusion modelsReinforcement learningMultimodalVisionNLPDistributed training

Company Brief

Tether.io

Builds tools and services to help companies hire, onboard, and manage remote or distributed teams across borders, focusing on payroll, compliance, and global employment workflows.

Industry: HR Tech

Website

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Tether.io

2 months ago

AI Research Engineer (Multi-Modal Reinforcement Learning) - 100% Remote Worldwide

✓ Verified Job

Canonical indexed version, validated from employer's careers page.

Source: Company careers pageValidated by: Fursa AI

Last checked: 4 hours agoStatus: Live

Job Summary

Workplace: Remote

Employment Type: Full time

Job Function: Education & Training

Key Responsibilities

•Conduct research on reinforcement learning algorithms for multimodal models, including diffusion-based approaches for image autoregressive models for multimodal understanding, and unified frameworks that integrate multiple modalities.
•Design and build reinforcement learning infrastructure that supports scalable, distributed training across multimodal systems while maintaining efficiency and reliability.
•Develop and refine reward modeling strategies that improve training stability, align model behavior with desired outcomes, and mitigate reward hacking and related failure modes.
•Create and curate multimodal simulation environments and datasets to support robust training, evaluation, and benchmarking of reinforcement learning systems.
•Design and conduct rigorous benchmarking and evaluation protocols to measure model performance, track progress against baselines, and validate improvements across multimodal tasks.

Key Requirements

•Master's degree in Computer Science or related field; PhD in Machine Learning, NLP, Computer Vision, or closely related discipline preferred, with a strong track record of AI research and publications in top-tier conferences.

Experience:MultimodalReinforcement learningAI research

Education:Bachelor's

Skills:ResearchProblem-solvingCommunication

Languages:English

Tech Stack:PyTorchDiffusion modelsReinforcement learningMultimodalVisionNLPDistributed training

Company Brief

Tether.io

Builds tools and services to help companies hire, onboard, and manage remote or distributed teams across borders, focusing on payroll, compliance, and global employment workflows.

Industry: HR Tech

Website