AI​/ML Platform Engineer

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. Our platform helps scientists and engineers build structured data foundations, digitize formulation and testing workflows, and apply AI to innovate faster, smarter, and at scale.

As our AI/ML Platform Engineer, you will build the foundational systems that enable

AI at the bench—the APIs, data pipelines, and workflow orchestration that turn ambitious AI capabilities into tools scientists canactually use.

We're building the lab of the future: a system where AI helps scientists invent faster, discover more, and optimize better. That future depends on a robust platform that can serve models in real-time, orchestrate complex multi-step pipelines, and integrate seamlessly with the data infrastructure that gives AI its understanding of chemistry. You'll be at the center of that work.

This is a foundational role with real influence. Our platform is robust but still in its early days—you'll have the opportunity to shape architecture decisions, introduce new technologies, and build systems that directly enable researchers at the world's largest chemical companies to leverage AI in ways that weren't possible before.

At Albert Invent, we value curiosity, rigor, and openness. We're writing the playbook for AI-augmented science together. If you want to build the infrastructure that makes that possible, we'd love to hear from you.

We are seeking an exceptional AI/ML Platform Engineer to join our AI/ML team. You'll own the APIs, data pipelines, and workflow orchestration that power our AI products—from real-time model inference to long-running optimization pipelines. This role sits at the intersection of backend engineering and data engineering: you'll build the services that serve up models, manage workflows, and connect AI capabilities to the structured data that makes them useful.

You'll work closely with our Active Learning and LLM/Agents team leads, translating their product vision into scalable, production-grade systems. The infrastructure you build will power model playgrounds for chemists, inverse design pipelines that optimize experiments across high-dimensional spaces, and orchestrated agent workflows that reason through complex scientific problems.

• Design and build high-performance Python APIs that serve models, manage workflows, and expose AI capabilities to the broader platform
• Architect backend services for scalability, reliability, and low latency
• Build integrations between AI/ML systems, graph databases, and external data sources

Pipeline & Workflow Orchestration

• Build andmaintainlong-running workflow pipelines using Ray and Temporal
• Design orchestration patterns for multi-step agent pipelines, batch inference, and numerical optimization workflows
• Ensure fault tolerance, graceful degradation, and efficient resource utilization

Data Infrastructure

• Architect andmaintaindata pipelines that feed AI/ML workflows
• Work with Neptune (graph), Redis, Dynamo
  
  DB, and other data stores to enable efficient data access patterns
• Build the connectors and transformations that give AI systems access to clean, structured, trusted data

Platform Reliability & Operations

• Implement observability including logging, metrics, tracing, and alerting
• Own system reliability—troubleshoot issues, conduct post-mortems, and continuously improve
• Design CI/CD pipelines and promote automation best practices
• Partner with ML researchers, data scientists, and product engineers to understand requirements and deliver production-ready infrastructure
• Collaborate closely with Active Learning and LLM/Agents team leads to align platform capabilities with product needs
• Contribute to architectural decisions that shape how AI gets built and shipped at Albert

• Deepexpertisein Python backend development and building production APIs
• Experience designing and operating data pipelines and workflow orchestration systems
• A builder's mindset—you want to create foundational systems that others build on
• Genuine curiosity about how your work enables scientific…