Develop bespoke software, APIs, data pipelines, and platform components to bring AI capabilities to life
Collaborate closely with data scientists, product team, and end-users to implement AI systems
Shape how new models are integrated and debug system bottlenecks
Help internal teams and customers derive value from model outputs as needs evolve
Requirements
Proven experience designing and building robust backend systems using technologies such as Node.js, Python, MongoDB, PostgreSQL, Redis, RabbitMQ, and Kafka
Demonstrated ability to scale production systems in cloud-native environments, familiarity with Kubernetes, NGINX, and container orchestration
Experience building and maintaining real-time applications, including working with WebSockets and event-driven architectures
Understands that solving problems means working across the stack from API development to frontend UIs and infrastructure-as-code
Have built real-world systems that expose or depend on ML models, including deployment or inference tooling (e.g. model serving, feature stores)
Strong software engineering fundamentals, with deep knowledge of algorithms, data structures, and system design
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