Founding Engineer

Job Summary - Founding AI Research Engineer

This is an equity-only founding engineering role for someone interested in building at the intersection of artificial intelligence, scientific research, and biological experimentation. We’re exploring new ways of developing AI systems that can help scientists understand complex concepts, model scientific phenomena, and improve how scientific work is performed. We’re seeking a Founding AI Research Engineer to join me and another technical cofounder to help design, train, evaluate, and study new models and research systems.

Our work focuses on developing AI as both an object of scientific study and a tool for scientific discovery. This may involve training foundation models from scratch, experimenting with new architectures and optimization methods, developing models for specialized scientific domains, and studying how models learn and represent scientific concepts. We’re also interested in understanding how AI systems can participate in scientific workflows, from hypothesis generation and computational modeling to experimentation, analysis, and evaluation.

Depending on the project, the work may span machine learning research, foundation model development, scientific computing, model evaluation, optimization, and research tooling. You’ll work closely with scientists, software engineers, computational researchers, and other technical collaborators while helping build the underlying research capabilities of an early-stage company.

Responsibilities

Assist with developing models and experiments involving:

• Training and experimenting with foundation models and specialized AI systems
• Model architectures, learning dynamics, and optimization techniques
• Scientific reasoning, representation learning, and concept formation
• Using AI systems to model or investigate scientific phenomena
• Evaluating AI performance across scientific tasks and workflows
• Computational modeling, simulation, and scientific data analysis
• Understanding relationships between model behavior, internal representations, and scientific concepts

Assist with executing the end-to-end process of developing research capabilities:

• Design, train, fine-tune, and evaluate machine learning models
• Develop scalable training and experimentation infrastructure
• Build reliable data pipelines for scientific and computational datasets
• Implement and test new architectures, training methods, and optimization techniques
• Develop evaluations for scientific reasoning and research workflows
• Create tools and visualizations for understanding model behavior and experimental results
• Work with scientists and engineers to translate research questions into computational experiments
• Formulate hypotheses and design controlled experiments around model capabilities and learning

Preferred Qualifications

• Experience or coursework in machine learning, computer science, applied mathematics, physics, computational science, or a related technical field
• Experience with Python, PyTorch, JAX, TensorFlow, or similar machine learning frameworks
• Interest in foundation models, scientific machine learning, optimization, or artificial intelligence research
• Experience training, fine-tuning, evaluating, or analyzing machine learning models
• Experience working with scientific, computational, or large-scale datasets
• Exposure to statistics, numerical methods, scientific computing, distributed systems, or computational modeling
• Ability to work across research and engineering problems in an early-stage environment
• Curiosity about how AI systems learn concepts and how they can be used to accelerate scientific understanding