AI Research Engineer (Multi-Modal & Vision) - 100% Remote Worldwide

4 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.
Improve model efficiency and deployability for resource-constrained environments through compression and optimization.
Design evaluation frameworks and benchmarks for model performance, robustness, and real-world task success.
Build and scale training workflows across distributed GPU infrastructure and resolve pipeline bottlenecks.
Contribute to and leverage open-source models, datasets, and tooling.
Track multimodal AI research and translate relevant findings into practical improvements.
Publish research findings in top-tier AI conferences and journals where applicable.

Bachelor’s 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 top AI conferences such as NeurIPS, ICML, ICLR, CVPR, or ECCV.
Excellent English communication skills.

100% remote work worldwide.
Opportunity to work with a small, high-caliber team on multimodal AI research and production deployment.
Direct impact within a fast-growing, lean global fintech and technology company.

201-500 employees