Build and maintain data catalog infrastructure that connects with BI tools, warehouses, and metadata platforms. Develop and own full-stack features, from backend services and data integrations to APIs and web interfaces. Create and maintain platform connectors and adapters to unify data and metadata across sources. Help define integration standards and best practices for cross-platform data workflows.

Lead a growing team responsible for structuring a diverse collection of multimodal datasets and providing various access patterns for internal developers including multi-media semantic search, entity search, and relational data primitives. This team plays a crucial role in powering most of Vannevar Labs' mature products, while also supporting new product initiatives, enabling internal developers to move faster by solving common problems.

As Canva scales change continues to be part of our DNA. The Discovery Platform sub-group focuses on maintaining high throughput machine learning and information retrieval systems and laying the groundwork for next generation of ML and generative AI capabilities. You'll scale out backend systems, build and maintain APIs and platform capabilities, contribute to experimentation tools and operational excellence.

Drivetrain is looking for a Backend Engineer to join our team to work on challenging problems in backend application development, algorithms, system design, and serving in production. You will work on Java, Spring, Hibernate, Redis, Elasticsearch, PostgreSQL, BigQuery, and AWS. As an early team member, you’ll help shape our company culture, engineering practices, and the product.

Magnet Forensics is looking for a Software Engineer to help design, build, and optimize their AI-powered search capabilities. You will design and improve search functionality that will surface critical leads and insights for forensic investigators, ensuring that search results are accurate, fast, and meaningful. You will work to develop scalable, high-performance search solutions.

You will enhance and maintain scalable LLM inference pipelines that transform communications into actionable deal assessments and insights. Responsibilities include improving and optimizing critical LLM inference pipelines, developing and implementing new AI features, enhancing monitoring systems, and scaling inference pipelines effectively. Collaboration with cross-functional teams is essential.