As a Software Engineer on the ML OSS Ecosystem Team, you will play a key role in building and maintaining our open-source MLflow platform to support machine learning workflows and enable users to train, deploy and monitor models at scale. Additionally, you will collaborate with the larger ML community to contribute to open-source projects and advance MLOps capabilities in the industry.

The Impact You'll Have
• Design and implement platform capabilities to support the ML development and productionization lifecycle including training, evaluation, deployment, monitoring, and management of machine learning models in MLflow
• Design and implement MLflow platform integrations with various frameworks in the ML ecosystem
• Collaborate with the ML community across the world to advance the state-of-the-art in MLOps.
• Ensure the latest ML tooling advancements are available to Databricks’ customers, thereby enabling organizations around the world to get more value from their data.
• Mentor and... guide junior engineers on the team by helping with project planning, technical decisions, and code and document review.

What We Look For
• BS (or higher) in Computer Science, or a related field
• 2+ years of hands-on experience in building production systems using at least one of the following programming languages: Java, Scala, or Python.
• Experience building and maintaining software tools and frameworks for machine learning, ideally in an open-source environment.
• Familiarity with ML and MLOps concepts and technologies, such as model training, deployment, and monitoring.
• [Preferred] Deep understanding and experience in working with Spark and MLflow and should be able to leverage them to build robust and scalable platforms to develop machine learning models.
• [Preferred] Significant contributions to open-source projects in the machine learning domain, such as SparkML, TensorFlow, PyTorch, MLflow, or other similar projects
Singapore

Salary Criteria