ML Scientist: Adversarial Robustness & Efficient Vision

Obsidian; Greater London; On-site; GBP 90,000 - 140,000; Full time

Job summary

Obsidian is seeking experienced machine learning researchers with hands-on experience training and improving end-to-end deep learning models across vision and language. You will tackle well-scoped empirical open‑ended ML research problems.

We value expertise in adversarial robustness, efficient computer vision, generative image modeling, multilingual pre‑training, and responsible LLM fine‑tuning, with a flexible, project‑based environment and competitive compensation.

Qualifications

• 3+ years of machine learning research experience (PhD counts)
• Strong experience with PyTorch, JAX, TensorFlow, or similar ML frameworks
• Degree from a top‑100 university, FAANG or comparable AI company experience, or impactful research publications or open‑source contributions

Responsibilities

• Train and improve deep learning models end‑to‑end for vision and language tasks.
• Address robustness to adversarial inputs and conversations.
• Compress models to meet size and latency budgets; diagnose training issues.

Skills

Adversarial Robustness

Efficient Computer Vision

Generative Image Modeling

LLM Fine-tuning & Alignment

Multilingual Pre-training

Uncertainty Estimation

Data Augmentation

Education

PhD or equivalent research track record

Top‑100 university degree

Tools

PyTorch

JAX

TensorFlow

Job description

Obsidian is seeking experienced machine learning researchers with hands-on experience training and improving end-to-end deep learning models across vision and language. You will tackle well-scoped empirical open‑ended ML research problems.

We value expertise in adversarial robustness, efficient computer vision, generative image modeling, multilingual pre‑training, and responsible LLM fine‑tuning, with a flexible, project‑based environment and competitive compensation.