Senior Machine Learning Research Scientist, Data and ML Innovation

Apple Inc

Confirmed live yesterday High trust

Quick summary

Work type: On-site
Location: Seattle, WA
Salary: $175,000–$308,500 / yr
Posted: 10 days ago
Freshness: Confirmed live yesterday
Nearby: 99+ roles within 25 mi

Market check

Salary context

Competitive pay

How this pay compares to similar roles

Similar $228k

This role $242k

$159k most similar roles pay here $325k

This role pays more than 53% of similar roles. Most pay $200,887–$254,750 — the shaded band above. At the midpoint, this role pays about $242k versus about $228k for comparable roles.

Based on 240 similar postings.

Employer

About Apple Inc

Apple Inc. is a multinational technology company known for designing and manufacturing consumer electronics, software, and online services, including the iPhone, Mac, iPad, and App Store. Industry: Consumer Electronics & Software

Apple Inc currently has 1984 open roles on FindRole.

Listed pay typically runs $175,000–$277,600 across 1590 roles with salary data.

Most-posted roles

View all roles at Apple Inc

At a glance

TL;DR · Senior Machine Learning Research Scientist, Data and ML Innovation

Role Posting Log in to save

AIML - Sr Machine Learning Research Scientist, Data and ML Innovation will join a small team of researchers performing fundamental research investigating foundation models for scientific domains. The role involves project definition, method development, experimental design, and running experiments to understand what foundation models do under the hood. You will analyze results, communicate findings to partner teams, and write papers for publication in top-tier conferences or journals. Key technical requirements include deep knowledge of foundation models, experience training them on complex datasets, and proficiency with Python, PyTorch, and Jax. The role also requires familiarity with vllm for inference, interpretability methods like activation patching or causal tracing, and Bayesian statistical methods for scientific inference. This position focuses on the specific challenge of understanding how foundation models function within scientific domains to solve practical problems.

Skills

Foundation Models Large Language Models Python PyTorch Jax vLLM Machine Learning Natural Language Processing Interpretability Methods Activation Patching Causal Tracing Experimental Design Scientific Inference

What you'll do

Design robust experiments and methods to understand the internal mechanics of foundation models.
Implement research methods and experimental designs into automated experiment pipelines.
Analyze and interpret results from conducted experiments to derive actionable insights.
Write and submit research papers for publication in top-tier machine learning conferences and journals.
Translate research findings into practical solutions for applied problems across various product areas.
Refine ambiguous research ideas into coherent, logically sound narratives for scientific communication.
Apply foundation models to complex datasets within specific scientific domains.

What we're looking for

PhD in computer science, statistics, physics, chemistry, electrical engineering, operations research, or other hard sciences.
At least 3 publications in top-tier machine learning, statistics, or natural language processing venues.
Deep knowledge of foundation models and experience training and applying them to complex datasets.
Experience designing experiments to understand how foundation models work.
Knowledge of Bayesian statistical methods for scientific inference.
Proficiency implementing ML models and experiments in Python and Pytorch/Jax.
Familiarity with interpretability methods like activation patching or causal tracing.
Ability to refine ambiguous research ideas into coherent, logically sound stories.