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Principal Research Scientist – Scaling

2 months, 2 weeks ago
United States
Full-time
Lead
AI Research Scientist
Software Development
Apache Spark Deep Learning Generative AI LLM Machine Learning MLflow Python PyTorch Reinforcement Learning
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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 226

Description

  • Lead and grow a multidisciplinary research team focused on LLM scaling, efficiency, and systems performance.
  • Define and execute the scaling research roadmap in alignment with Databricks’ strategic objectives.
  • Drive algorithmic innovations for large-scale training and inference, including optimizers, low-precision techniques, and model adaptation methods.
  • Oversee the design and execution of large-scale experiments and benchmark results against state-of-the-art methods.
  • Optimize distributed training, parallelism, memory management, and hardware utilization in collaboration with systems and infrastructure teams.
  • Translate research breakthroughs into customer-facing capabilities in the Databricks AI platform.
  • Establish metrics, evaluation protocols, and best practices for scaling-focused research and drive adoption across the organization.
  • Champion responsible deployment by ensuring model behavior, reliability, and safety remain first-class considerations.
  • Work hands-on with the team to develop high-quality Python and PyTorch code for research, prototyping, and production integration.
  • Mentor and develop research scientists and engineers through technical guidance and career support.

Requirements

  • Proven ability to lead a research team developing novel techniques for foundation model efficiency or related topics.
  • Strong track record of industry impact.
  • Deep expertise in at least one of: generative AI, LLMs, distributed ML systems, model optimization, or responsible AI.
  • Strong emphasis on scaling and efficiency for large-scale neural networks.
  • 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, with ongoing collaborations or conference service such as PC or area chair roles (preferred).
  • First-author publications at top ML/systems conferences such as ICLR, ICML, NeurIPS, or MLSys, or influential open-source contributions / widely used deployed systems, especially in optimization or efficiency (preferred).

Benefits

  • Competitive base salary range of $280,000 to $350,000 USD.
  • Eligibility for an annual performance bonus.
  • Eligibility for equity as part of the total compensation package.
  • Comprehensive benefits and perks offered regionally.
  • Compensation may be adjusted based on skills, experience, certifications, training, and work location.

Interested in this position?

Apply directly on the company website

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