Databricks

Senior GenAI Research Scientist - AI Efficiency & Optimization

Databricks$166K — $230K *
Enterprise Technology
Less than 5 years of experience
Job Overview by Ladders

Qualifications

  • MS/PhD in Computer Science or similar field with strong machine learning foundations
  • Proficient in writing efficient Python and PyTorch code
  • Track record of first-author publications in top ML/systems conferences focused on optimization
  • Strong understanding of model efficiency in training and reinforcement learning
  • Experience in large-scale neural network training or inference

Responsibilities

  • Lead independent research on foundation model efficiency in training and reinforcement learning
  • Experiment to validate hypotheses and benchmark against leading approaches
  • Innovate algorithms for large-scale neural network training and inference
  • Optimize ML systems focusing on distributed training and memory efficiency
  • Implement practical solutions for research problems

Benefits

  • Comprehensive benefits package catering to diverse employee needs
  • Eligibility for annual performance bonuses
  • Equity opportunities in company ownership
  • Supportive work culture promoting collaboration and innovation
Full Job Description
Job Description

As a Sr. Research Scientist on the Scaling team, you will be responsible for keeping up with the latest developments in deep learning and advancing the scientific frontier by creating new techniques that go beyond the state of the art. You will work together on a collaborative team of researchers and engineers with diverse backgrounds and technical training. And most importantly, you will love our customers: our goal is to make our customers successful in applying state-of-the-art LLMs and AI systems, and we encode our scientific expertise into our products to make that possible.

The Impact you will have

As a Sr. Research Scientist on the AI Research Team at Databricks, You Will:
  • Define and lead independent research agendas on foundation model efficiency in model training and reinforcement learning, conducting experiments to empirically validate hypotheses and benchmark against state-of-the-art approaches
  • Drive algorithmic innovations for large-scale neural network training or inference (e.g., novel optimizers, low-precision techniques, model adaptation methods)
  • Optimize ML systems for distributed training, memory efficiency, and compute efficiency through hands-on implementation.

What We Look for
  • MS/PhD in Computer Science or related field with strong foundations in machine learning and systems
  • Proven ability to write high-quality, efficient code in Python and PyTorch for research implementation and experimentation
  • Strong preference for candidates with first-author publications at top ML/systems conferences (ICLR, ICML, NeurIPS, MLSys) focused on optimization or efficiency.


Pay Range Transparency

Databricks is committed to fair and equitable compensation practices. The pay range(s) for this role is listed below and represents the expected salary range for non-commissionable roles or on-target earnings for commissionable roles. Actual compensation packages are based on several factors that are unique to each candidate, including but not limited to job-related skills, depth of experience, relevant certifications and training, and specific work location. Based on the factors above, Databricks anticipates utilizing the full width of the range. The total compensation package for this position may also include eligibility for annual performance bonus, equity, and the benefits listed above. For more information regarding which range your location is in visit our page here.

Local Pay Range

$166,000-$230,000 USD

BenefitsAt Databricks, we strive to provide comprehensive benefits and perks that meet the needs of all of our employees. For specific details on the benefits offered in your region click here.

About Databricks

Databricks is a unified analytics platform that provides data engineering, collaborative data science, and machine learning capabilities. The company was founded in 2013 by the original creators of Apache Spark, a popular open-source big data processing engine. Databricks provides a cloud-based platform that allows data teams to collaborate and build data pipelines, run machine learning models, and perform advanced analytics. The company has raised over $1 billion in funding and is valued at $38 billion as of November 2021.
Learn more about Databricks
Size
2,000 employees
Industry
Founded
2013

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