ML Research Scientist

About the Company

Merge Labs is a frontier research lab with the mission of bridging biological and artificial intelligence to maximize human ability, agency and experience. We’re pursuing this goal by developing fundamentally new approaches to brain-computer interfaces that interact with the brain at high bandwidth, integrate with advanced AI, and are ultimately safe and accessible for anyone to use.

Responsibilities

• Build the scientific and engineering scaffolding for active-learning and closed-loop optimization, including data ingestion, ML modeling, and library design
• Collaborate with wet-lab scientists to define tractable optimization objectives and encode domain specific priors and constraints
• Prototype representation-learning and acquisition-strategy using internal and public datasets
• Integrate ML models with experimental data streams and serve to non-domain experts
• Extend ML frameworks to handle multi-objective or constrained optimization problems
• Stay up-to-date with the latest research in Bayesian optimization, active learning, and RL
• Contribute to the long-term research roadmap and serve as a thought-leader

Requirements

• Strong grounding in probabilistic modeling, uncertainty quantification, and representation learning
• Working knowledge of preference optimization and transfer-learning strategies
• Proficiency in Python, PyTorch, BoTorch, or Pyro
• Experience writing clean, reproducible production grade code
• Experience bridging machine learning and experimental science with sparse, noisy, or high-cost data
• Collaborative, systems-level mindset

Preferred Qualifications

• Familiarity with neuroscience
• Familiarity with language or state-space models