Senior Staff AI 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.

About the role

We are seeking a highly motivated and talented individual with a passion for AI/ML engineering and agent technologies. In this role, you will unleash your creativity, intelligence, and curiosity to build scalable AI systems that empower researchers and chemists at leading chemical and materials organizations to push the boundaries of innovation.  

As an ML Engineer specializing in LLMs and agent technologies, you will play a critical role in our mission to streamline workflows and provide robust, scalable solutions that support AI/ML capabilities for thousands of researchers worldwide. This role is central to the development of autonomous systems and tools tailored to chemical and materials science applications.  

What you'll do

We are seeking an exceptional ML Engineer with a focus on LLMs and RAG systems. This role prioritizes designing and developing scalable, fault-tolerant AI systems while maintaining a strong focus on domain-specific AI solutions. You will play a critical role in building robust infrastructure to support high-performance applications and tools, enabling seamless data integration and transformation to power AI/ML capabilities in chemical and materials science.  

Scalable AI System Development:  

• Design, build, and maintain scalable, fault-tolerant AI systems leveraging OpenAI and Anthropic models.  

• Develop RAG architectures to ensure efficient, high-performance information retrieval tailored to chemical and materials science.  

• Optimize system performance to handle large-scale data and application demands.  

AI Agent Development:  

• Build and maintain intelligent AI agents using modern frameworks.  

• Collaborate with domain experts to refine agent capabilities for specific scientific workflows.  

Data Engineering and Integration:  

• Architect and maintain vector database solutions for efficient data storage and retrieval.  

• Develop pipelines for ingestion, transformation, and storage to enable AI/ML workflows.  

• Collaborate with platform and ML engineers to integrate AI/ML models with backend systems.  

System Reliability and Fault Tolerance:  

• Implement robust error-handling, monitoring, and alerting mechanisms to ensure system resilience.  

• Troubleshoot and resolve system bottlenecks and failures.  

CI/CD and Deployment Pipelines:  

• Design, implement, and maintain CI/CD pipelines for AI systems and data workflows.  

• Promote automation and best practices to enhance the development lifecycle.  

Adoption of Emerging Technologies:  

• Stay informed on the latest trends and tools in AI/ML engineering and agent technologies.  

• Introduce and implement new technologies to improve system scalability, data integration, and developer productivity.  

Collaboration and Cross-Functional Teamwork:  

• Work closely with AI/ML, data engineering, and platform teams to understand and deliver on technical requirements.  

• Contribute to architectural decisions that impact the overall platform ecosystem.  

You will have

• A strong passion for AI/ML engineering and scalable data systems.  

• An ability to prioritize system scalability and fault tolerance while focusing on innovati