Senior Research Scientist (Bayesian AI)

Role Overview

Lead research initiatives in Bayesian Deep Learning and Uncertainty Quantification. You will publish in top‑tier conferences (NeurIPS, ICML, ICLR) and partner closely with engineering to translate theoretical breakthroughs into reliable, production‑grade systems used in safety‑critical and high‑impact domains.

What You’ll Do

• Develop novel Bayesian neural architectures and inference strategies for calibrated uncertainty under distribution shift and data scarcity.
• Own research projects end‑to‑end: problem framing, literature review, experimentation, paper writing, and open‑sourcing artifacts where appropriate.
• Partner with platform and product teams to harden probabilistic models for deployment (performance, robustness, monitoring, and drift detection).
• Advance the state of the art via publications, preprints, and talks; engage with the community through reviews and reproducibility efforts.
• Mentor junior researchers and engineers; cultivate rigorous, inclusive research practices and documentation.

Minimum Qualifications

• Ph.D. in Computer Science, Statistics, Mathematics, or closely related field (or equivalent research experience).
• Strong publication record in Bayesian Deep Learning or Probabilistic Machine Learning (e.g., NeurIPS/ICML/ICLR/UAI/AISTATS/JMLR).
• Proficiency in Python and modern ML frameworks (PyTorch preferred; TensorFlow acceptable).
• Hands‑on experience with variational inference (e.g., amortized VI), MCMC/SGLD/HMC, ensembles, or Laplace/linearized approximations.

Preferred Experience

• Uncertainty calibration, out‑of‑distribution detection, reliability for safety‑critical systems, or risk‑aware decision‑making.
• Large‑scale training and evaluation, experiment tracking, and reproducible pipelines.
• Hands‑on deployment experience (e.g., TorchScript, Triton/TorchServe) and performance optimization.
• Strong software engineering fundamentals: testing, code review, documentation, and CI workflows.

Benefits & Perks

• Remote‑first with periodic on‑site research weeks in Philadelphia.
• Competitive compensation; meaningful impact and authorship opportunities.
• Budget for conferences, papers, and open‑source contributions.
• Well‑being and continuous learning support.

How We Hire

• Introductory conversation (mutual fit, interests, logistics).
• Technical deep dive on your prior work and research direction.
• Collaborative problem exploration or paper discussion.
• Team conversations and final review.

We respect your time. Whenever possible, we tailor interviews around your research artifacts (papers, code, demos).

Location & Work Authorization

Remote within the US; periodic travel to Philadelphia, PA for team events. Work authorization as applicable to the role; sponsorship considered for exceptional candidates.

Equal Opportunity & Accessibility

TeraSystemsAI is an equal opportunity employer. We celebrate diversity and are committed to an inclusive environment for all teammates. We provide reasonable accommodations in our hiring process. Request assistance at careers@terasystems.ai.