Axiom is building AI systems for drug safety and toxicity assessment to help drug discovery teams bring new medicines to patients faster by reducing drug program failures caused by toxicity.
Requirements
- Strong generalist software engineer with experience across cloud infrastructure, machine learning, backend systems, distributed systems
- Built and deployed production systems used by large enterprise businesses
- Designed and developed large-scale machine learning systems covering data access, training, evaluation, and deployment
- Handled the “messy” parts of ML deployment, such as evaluation pipelines, versioning, and monitoring
- Built LLM-powered data systems, with a focus on research workflows and information retrieval
- Built SaaS products that store and process large volumes of customer data
- Experience with enterprise ML software
Responsibilities
- Design and build the core infrastructure that powers Axiom’s enterprise ML systems, including model evaluation/deployment, model inference/serving, and customer data management
- Architect scalable systems for inference, storage, and retrieval of chemical, biological, and clinical data
- Deploy large-scale reasoning agents from research environments into production, integrating them into on-prem customer-facing products and infrastructure
- Automate ETL from diverse sources
- Build LLM-driven literature research and data platforms
- Scale inference of image and graph neural networks
- Ensure the integrity of datasets that drive critical decisions internally and externally
Other
- Lead Axiom’s evolution into a world-class engineering company focused on enterprise ML software
- Teach and empower scientists across ML, chemistry, and biology to become great engineers by instilling a great engineering culture
- Enjoys working with enterprise customers and simplifying complex technical solutions to meet their needs
- Invested in team growth particularly when it comes to building strong engineering culture across the company
- Passionate about collaborating with researchers and scientists, helping them become strong engineers
