Member of Technical Staff – Causal Inference Research

About the role

Ataraxis AI is building clinical AI tools that make disease outcomes predictable. As a Member of Technical Staff focused on Causality, you will design and implement cutting‑edge causal inference methods that drive treatment‑effect modeling for precision medicine.

Key responsibilities

• Design and implement novel causal inference algorithms for treatment‑effect estimation.
• Translate state‑of‑the‑art research papers into production‑ready Python/PyTorch code.
• Build robust evaluation frameworks for model validation on observational and randomized trial data.
• Co‑author research papers and conference abstracts to disseminate findings.
• Collaborate with a multidisciplinary team of engineers, scientists, and clinicians.
• Mentor junior team members and contribute to a flat, high‑impact culture.

Required profile

• PhD in Causality, Statistics, Machine Learning, or a closely related field.
• Deep understanding of causal inference concepts and experience with both observational and randomized trial datasets.
• Track record of publishing in top AI or statistics venues (e.g., ICML, ICLR, NeurIPS, top journals).
• Strong attention to detail and ability to drive research tasks to completion.

Required skills

• Python programming
• PyTorch deep‑learning framework
• Core machine‑learning concepts
• Statistics, linear algebra, probability theory
• Causal inference methods
• Survival analysis
• Multi‑modal learning

What we offer

• Opportunity to shape AI‑driven healthcare solutions.
• Flat organizational structure with rapid impact.
• Collaboration with leading AI pioneers and oncologists.
• Competitive compensation backed by $24M+ of venture funding.