OWN THE ENGINEERING. MAKE THE SCHEDULING MAGIC HAPPEN.

At Doodle, we’re building the future of scheduling and productivity, tackling complex challenges at the intersection of human collaboration and digital efficiency. We believe in crafting elegant solutions to intricate problems, and we’re looking for passionate Machine Learning Engineers who share this drive.
You’re more than a model-builder; you’re a problem-solver, an innovator, and a continuous learner who thrives on turning data into impact. You’ll shape and optimize the intelligence behind our scheduling platform—designing, training, and deploying models that understand human behavior, adapt to complex constraints, and deliver seamless user experiences

• Design, build, and deploy production-ready LLM-powered systems that support multi-step task automation, tool use, and context-aware reasoning within our product.
• Implement MLOps pipelines with best practices in mind, focusing on automation, monitoring, and continuous integration/continuous delivery (CI/CD).
• Contribute to our core backend services built with Java and Go, ensuring seamless integration of AI models.
• Ensure the performance and reliability of models over time by implementing robust monitoring solutions.
• Collaborate closely with Data Scientists and Principal Engineers to translate model prototypes and research into scalable, shippable products.
• Collaborate on our AI strategy and roadmap, identifying and implementing the best-suited neural network architectures—whether they are LLMs or other models—for a given task.Bridge the gap between model development and product delivery by embedding AI capabilities into real user workflows, ensuring the technical architecture supports meaningful product outcomes.