Senior ML Infrastructure Engineer

Databricks is looking for a Senior ML Infrastructure Engineer to build and scale the platform that powers machine learning innovation for thousands of companies worldwide. You will play a critical role in designing, developing, and maintaining the robust, scalable, and efficient infrastructure required for training and deploying large-scale machine learning models. This is an opportunity to work on a high-impact platform at the heart of the AI revolution. Responsibilities: - Design, build, and maintain scalable and reliable ML infrastructure, including distributed training systems, model serving platforms, and data pipelines. - Collaborate with ML engineers and data scientists to understand their infrastructure needs and provide solutions. - Optimize infrastructure performance, cost, and resource utilization. - Develop automation tools and frameworks for ML workflows. - Troubleshoot and resolve complex infrastructure issues in production environments. Qualifications: - Bachelor's or Master's degree in Computer Science, Engineering, or a related field. - 5+ years of experience in software engineering, with a focus on distributed systems, cloud infrastructure, or ML platforms. - Strong programming skills in Python and/or Scala/Java. - Experience with cloud platforms (AWS, Azure, GCP) and containerization technologies (Docker, Kubernetes). - Familiarity with ML frameworks (e.g., PyTorch, TensorFlow) and MLOps concepts. - Experience with big data technologies (e.g., Spark, Hadoop) is a plus. Benefits: - Competitive salary, stock options, and performance bonuses. - Comprehensive health, dental, and vision benefits. - Generous paid time off and parental leave. - Professional development and learning opportunities. - Dynamic and fast-paced work environment.