Principal Research Scientist - AI Scaling & Optimization

1 week, 3 days ago
Full-time
Lead
DevOps and Infrastructure
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

Description

  • Lead and grow a multidisciplinary research team focused on LLM scaling, efficiency, and systems performance.
  • Define the scaling research roadmap in alignment with Databricks’ strategic objectives.
  • Drive algorithmic innovations for large-scale neural network training and inference, including optimizers, low-precision techniques, and adaptation methods.
  • Optimize end-to-end ML systems for distributed training, reinforcement learning, memory efficiency, and compute efficiency.
  • Partner with product and engineering teams to turn research breakthroughs into production platform capabilities.
  • Oversee large-scale experiments, benchmarking, and evaluation of trade-offs in quality, latency, throughput, and cost.
  • Establish metrics, evaluation protocols, and best practices for scaling-focused research.
  • Champion responsible and robust deployment of scaling innovations.
  • Represent Databricks AI research externally through publications, talks, and collaborations with academia and open source communities.
  • Mentor and develop researchers and engineers through technical guidance and career support.

Requirements

  • Proven ability to lead a research team developing novel techniques for foundation model efficiency and related topics.
  • Strong track record of industry impact in large-scale machine learning or AI research.
  • Deep expertise in at least one of: generative AI, LLMs, distributed ML systems, model optimization, or responsible AI.
  • Strong programming skills and demonstrated ability to write high-quality, efficient code in Python and PyTorch.
  • Demonstrated ability to translate research innovation into scalable product capabilities with product and engineering teams.
  • Excellent communication, leadership, and stakeholder management skills.
  • Experience influencing cross-functional roadmaps and aligning research with business impact.
  • Prior work at the intersection of systems and ML, such as distributed training frameworks, compiler and kernel optimization, or memory-/compute-efficient model design (preferred).
  • Strong industry and academic network in large-scale ML, including collaborations or service at top conferences (preferred).
  • A strong record of research impact such as first-author publications, influential open-source contributions, or widely used deployed systems, especially in optimization or efficiency (preferred).

Benefits

  • Base salary range of $270,000 to $350,000 USD.
  • Eligibility for annual performance bonus.
  • Eligibility for equity.
  • Comprehensive benefits and perks package.
  • Opportunity to work at a company with offices around the globe.
  • Access to a remote location-based pay range and compensation determined by experience, certifications, and work location.

Interested in this position?

Apply directly on the company website

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