Head of Bio AI - Radial

About Astera:

Astera is a private foundation on a mission to steer science and technology toward an abundant future. We believe the coming years will bring an era of unprecedented scientific and technological advancement as exponential progress in AI converges with central advances in other fields to dramatically accelerate innovation. This inflection point provides an unparalleled opportunity to fundamentally rethink the institutions, systems, and tools that drive scientific progress.

Unlike traditional non-profit research organizations, Astera funds and operates projects supported by Astera operate like high-velocity startups, allowing us to focus on ambitious goals, match structure to problem, and attract strong technical talent and leadership. You can read more about our mission, vision, and programming here.

Radial is a research organization within Astera focused on rethinking life science research at a systems level. The systems that enable how we fund, do, and build upon science have long needed an update. At Radial, we design, fund, and operate programs that tackle foundational scientific problems while simultaneously testing better ways to do science. We're looking for people who are willing to take big risks, build useful things and share their learnings in the open.

Mission

Hire a founding technical leader to serve as the CEO’s technical co-pilot; the person who co-architects Radial’s scientific and technical direction, builds the AI and computational infrastructure across programs, and sets the technical bar through their own hands-on work. This is a building role: the Head of Bio AI will personally drive early prototypes, make critical architecture decisions, and help determine what Radial builds, how it builds it, and the standards to which it holds itself.

1. Technical Architecture & Program Leadership

• Establish AI and computational architecture across current and future programs, beginning with DiffUSE and its expansion across multiple structural biology data modalities.

• Shape which foundational bottlenecks Radial addresses and how they become durable technical systems.

• Help make build-vs-fund-vs-partner decisions across Radial’s program portfolio.

2. Hands-On Building

• Conceive, architect, and directly prototype early modeling systems and core infrastructure.

• Design scalable training workflows, data pipelines, validation frameworks, and evaluation benchmarks.

• Evolve capabilities from early prototyping to production-grade, open platforms the scientific community can build on.

3. Team & Culture

• Build a high-caliber AI and engineering team, starting small and scaling deliberately.

• Set the technical bar through hands-on contribution and architectural authorship.

• Establish a culture of technical rigor, intellectual honesty, and disciplined experimentation.

4. Ecosystem & Impact

• Engage leading scientific collaborators and build technically rigorous partnerships.

• Represent Radial’s technical vision within the AI and life sciences communities.

• Ensure outputs are structured and shared as durable public goods.

Functional Expertise

• Deep expertise in modern ML: large-scale training, representation learning, generative modeling (diffusion, transformers, foundation models).

• Track record of translating ideas into working, scalable systems.

• Understanding of the interplay between machine learning and physics-based modeling

• Direct experience formulating and solving inverse problems, including familiarity with ill-posedness, regularization strategies, and the trade-offs between learned and model-based reconstruction approaches

• Experience building and iterating on ML pipelines for large-scale, data-intensive problems, including efficient data ingestion, preprocessing of high-dimensional inputs, and training workflows that scale across distributed compute resources

• Systems-level thinking across data generation, modeling, infrastructure, and experimentation.

• Experience designing technical platforms intended to endure and compound over time.

• Scientific range beyond a single modality can engage across problem domains.

Leadership Attributes

• Has managed small…