onsite
Machine Learning Engineer Graduate Trust & Safety - CV/NLP/Multimodal LLM
ML Engineer
Join a research‑focused team to develop trustworthy AI systems, applying computer vision, NLP, and multimodal large language models with active learning and distributed training techniques.
About the role
Key Responsibilities
- Design and implement state‑of‑the‑art computer vision and NLP models for trust and safety applications.
- Develop active‑learning pipelines to efficiently label and incorporate new data streams.
- Scale model training across multi‑GPU/cluster environments using distributed training frameworks.
- Integrate multimodal large language models to analyze text, image, and video content jointly.
- Collaborate with cross‑functional research teams to evaluate model robustness, bias, and safety metrics.
Requirements
- PhD (or near‑completion) in Machine Learning, Computer Vision, NLP, or a related field.
- Strong programming skills in Python and experience with deep‑learning libraries such as PyTorch or TensorFlow.
- Hands‑on experience with distributed training (e.g., Horovod, DeepSpeed, or PyTorch Distributed).
- Demonstrated research or project work on active learning, multimodal modeling, or large language models.
- Ability to translate research findings into production‑ready code and evaluate safety‑critical performance.
Skills
machine learningcomputer visionnatural language processing