Albert’s mission is to digitalize the world of chemistry. Using data and machine learning, Albert enables R&D organizations to dramatically accelerate the invention of new materials. Backed by Index.
About the role
As our Backend & Infrastructure Engineer, you will architect and build the core systems that power everything our AI/ML team delivers—the APIs, infrastructure, and distributed systems that make intelligent capabilities possible at scale. This is a foundational role: you'll shape how AI gets built and shipped here.
What they're looking for
- Design, deploy, and maintain Kubernetes infrastructure supporting AI/ML workloads
- Manage containerized services, autoscaling, networking, and resource optimization
- Design and build high-performance Python APIs and services using FastAPI or similar frameworks
- Architect backend systems for scalability, reliability, and low latency
- Build integrations between AI/ML systems and the broader Albert platform
- Build and operate distributed systems that handle compute-intensive and high-throughput workloads
More about this role
As our Backend & Infrastructure Engineer, you will architect and build the core systems that power everything our AI/ML team delivers—the APIs, infrastructure, and distributed systems that make intelligent capabilities possible at scale. This is a foundational role: you'll shape how AI gets built and shipped here.
We are seeking a highly motivated and talented individual with deep expertise in Python backend development, Kubernetes, and distributed systems. You'll be embedded with ML engineers and researchers, building robust systems that turn ambitious AI ideas into production realities—whether that's powering agent-based workflows, scaling inference, or enabling scientific computing pipelines. The infrastructure you build will directly enable researchers at the world's largest chemical and materials companies to leverage AI in ways that weren't possible before—accelerating discovery, enabling inverse design of novel materials, and transforming how science gets done.
- Design, deploy, and maintain Kubernetes infrastructure supporting AI/ML workloads
- Manage containerized services, autoscaling, networking, and resource optimization
- Design and build high-performance Python APIs...
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