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Staff Software Engineer - AI Research Infrastructure

4 days, 8 hours ago
United States
Full-time
Senior
Infrastructure Engineer
DevOps and Infrastructure
Apache Spark C++ Go Java Kubernetes LLM MLflow Rust Scala
Apply Now
Databricks

Databricks

Databricks is the pioneering data intelligence platform, empowering organizations worldwide to solve complex data challenges with AI-driven analytics solutions.

IT Services
1K-5K
Founded 2013
$4450M raised
View All Jobs 190

Description

  • Design and implement infrastructure for large-scale experiments, data processing, and model training across HPC clusters, GPU fleets, and cloud-based systems.
  • Build abstractions for job submission, scheduling, and monitoring that help researchers move from idea to large-scale experiment quickly.
  • Develop tooling that improves research developer productivity, including experiment management systems and CI/testing infrastructure for research code.
  • Turn experimental workloads into robust, repeatable pipelines in partnership with research scientists, ML engineers, and platform teams.
  • Improve reliability, efficiency, and security across research infrastructure and development workflows.
  • Influence the long-term roadmap for research computation, including how models are trained, evaluated, and shipped to customers.
  • Serve as a technical mentor and force multiplier for engineers working on compute, infrastructure, and AI systems.
  • Develop and run the research stack that supports Databricks AI Research workloads at scale.

Requirements

  • BS, MS, or PhD in Computer Science or a related field.
  • 5+ years of software engineering experience.
  • Substantial experience with large-scale distributed systems or infrastructure.
  • Deep experience building and operating distributed systems, data pipelines, or large-scale backend services.
  • Experience with GPUs, clusters, or major cloud providers is strongly preferred.
  • Proficiency in one or more systems programming languages such as C++, Rust, Go, Java, or Scala.
  • Experience with cluster schedulers, resource managers, or large-scale job orchestration systems such as Kubernetes, Slurm, Ray, or custom internal systems.
  • Understanding of modern ML training and inference workflows, including distributed training, model parallelism, fine-tuning, and evaluation.
  • Ability to move quickly and pragmatically while maintaining operational excellence.
  • Strong communication skills and ability to translate between research needs and infrastructure realities.

Benefits

  • Annual performance bonus eligibility.
  • Equity eligibility as part of total compensation.
  • Base salary range of $190,000 to $270,000 USD.
  • Comprehensive benefits and perks package.
  • Support for fair and equitable compensation practices.
  • Global company with offices around the world.

Interested in this position?

Apply directly on the company website

Apply Now

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