AI Research Engineer (Multi-Modal & Vision)
Tether Operations Limited3 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 high-quality multimodal datasets for domain-specific tasks.
- Adapt models for resource-constrained environments using compression and optimization techniques.
- Build evaluation frameworks and benchmarks for model performance, robustness, and real-world task success.
- Build and scale training workflows across distributed GPU infrastructure.
- Identify and resolve training-pipeline bottlenecks to improve model quality on target benchmarks.
- Contribute to and leverage open-source models, datasets, and tooling.
- Track multimodal learning and vision-language research and translate findings into practical improvements.
- Publish research findings in top-tier AI conferences and journals where applicable.
Requirements
- Degree in Computer Science, Machine Learning, or a related field; a master’s 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 results on standard benchmarks or real-world tasks.
- Experience adapting models for resource-constrained environments.
- Proven open-source contributions in multimodal AI on GitHub or HuggingFace.
- Publications at top AI conferences such as NeurIPS, ICML, ICLR, CVPR, or ECCV.
- Excellent English communication skills.
Benefits
- Remote work from anywhere in the world.
- Opportunity to work with a small, high-caliber AI team on multimodal models for production deployment.
- Opportunity to contribute to open-source AI and publish research.
Categories
AI ResearchML Engineering