Science researcher

We’re looking for smart and curious individuals from industry and academia to join our client's growing AI Lab and push the boundaries of applied deep learning in trading.

On their AI team, you’ll build and train deep learning models that directly power their trading strategies, supported by a massive and rapidly expanding compute cluster (thousands of H100s/200s). The challenges here are unique: ultra-low latency, vast and noisy datasets, constantly shifting dynamics, and tight feedback loops. These constraints demand original thinking and new techniques.

Researchers, engineers, and traders work closely together (often side by side) to train models, build systems, and run live strategies. One day you might be optimising training performance across thousands of GPUs; the next, you’re analysing how a model trades in production or designing a new architecture to capture subtle market signals.

They will rely on your deep knowledge of deep learning, whether your background is in LLMs, recsys, image models, RL agents, or classical methods, to help shape the next generation of their ML-driven trading. You’ll also contribute to hiring, mentor teammates, and share insights from the broader research community through papers, internal talks, and conference travel.

Who We’re Looking For

We’re open to a range of backgrounds and experiences, but the ideal candidate will have:

• An advanced degree in machine learning, statistics, applied math, or a related discipline; or equivalent experience in industry applying ML to challenging problems
• Expertise in one or more of: deep learning, reinforcement learning, non-convex optimisation, approximate inference, NLP, or Bayesian methods
• Strong programming skills, ideally in Python, with experience using tools like NumPy, Pandas, JAX, PyTorch or TensorFlow
• A strong publication record in top-tier venues (e.g., NeurIPS, ICML, ICLR) or competitive performance in ML challenges such as Kaggle or similar platforms
• The ability to independently formulate research questions and design experiments to answer them
• A desire to work on applied problems where real-world performance and feedback matter

What They Offer

• Highly competitive compensation and generous performance-based bonuses
• Access to extensive compute resources, including large-scale GPU clusters
• A collaborative and intellectually stimulating research environment
• 30 days of paid leave annually
• Employer pension contributions
• Daily catered lunch and barista service
• Flexible work culture with a focus on sustainability and well-being
• Comprehensive healthcare and life insurance coverage
• Monthly team events and regular conference attendance

At Adamas Knight, we are committed to creating an inclusive culture. We do not discriminate based on race, religion, gender, national origin, sexual orientation, age, veteran status, disability, or any other legally protected status. Diversity is highly valued, and we encourage applicants from all backgrounds to apply.