AIML - Sr Machine Learning Research Scientist, Data and ML Innovation

Socket.dev; Seattle (WA); On-site; USD 140,000 - 190,000; Full time

Job summary

Socket.dev is seeking a Research Scientist to join a team exploring foundation models for scientific domains. You will define projects, develop methods, design experiments, run studies, and analyze results.

You will contribute to papers for publication and translate findings into practical product directions, with opportunities to collaborate with partner teams across Apple.

Qualifications

• PhD in CS, statistics, physics, chemistry, EE, or OR; other hard sciences may be considered.
• 3 publications in top-tier ML, statistics, or NLP venues.
• Deep knowledge of foundation models and training them on real datasets; publications or code.
• Experience designing experiments to understand foundation models.
• Knowledge of Bayesian methods for scientific inference.

Responsibilities

• Perform fundamental research on foundation models for scientific domains, defining projects, method development and experimental design.
• Run experiments, analyze and interpret results, and write papers for publication.
• Collaborate with partner teams across Apple to translate findings into applied problems.

Skills

Deep knowledge of foundation models

Experiment design

Bayesian statistics for inference

Education

PhD required

Tools

Python

PyTorch

JAX

vLLM

Job description

Would you like to join a team curious about understanding how foundation models work and to expand their capabilities in scientific domains? We perform and publish novel research and apply our findings to drive product directions. If you like designing clever approaches to understanding complex phenomena and using that knowledge to solve practical problems then this is the position for you.

Description

In this research scientist role you will join a small team of researchers performing fundamental research investigating foundation models for scientific domains. You will be involved in all aspects of performing research including project definition, method development, and experimental design. You will also run your own experiments, then analyze and interpret the results. You will take an active role in writing papers for publication and also using our findings to solve applied problems. You will also have the opportunity to collaborate with partner teams across Apple.

Minimum Qualifications

• PhD in computer science, statistics, physics, chemistry, electrical engineering, or operations research. Other hard sciences may also be considered.
• 3 publications in top-tier machine learning, statistics, or natural language processing venues.
• Deep knowledge of foundation models and experience training them and applying them to real, complex datasets as demonstrated through publications or code repositories.
• Experience designing experiments to understand how foundation models work.
• Knowledge of Bayesian statistical methods and how they are used for scientific inference.

Preferred Qualifications

• Experience with large language models and – both training them and using tools like vllm for inference.
• Proficient implementing ML models and experiments in Python and Pytorch/Jax.
• Familiarity with interpretability methods like activation patching/causal tracing.
• Demonstrate the ability to refine ambiguous research ideas to construct a coherent and logically sound story.