Data Scientist - Synthetic Data and ML Evaluations - Special Projects

Apple Inc

Quick summary

Work type: On-site
Location: Cupertino, CA
Salary: $126,800–$220,900 / yr
Posted: 55 days ago
Nearby: 99+ roles within 25 mi

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Competitive pay

How this pay compares to similar roles

Similar $168k

This role $174k

$115k most similar roles pay here $233k

This role pays more than 58% of similar roles. Most pay $126,800–$208,826 — the shaded band above. At the midpoint, this role pays about $174k versus about $168k for comparable roles.

Based on 239 similar postings.

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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 1723 open roles on FindRole.

Listed pay typically runs $162,500–$272,100 across 1398 roles with salary data.

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At a glance

TL;DR · Data Scientist - Synthetic Data and ML Evaluations - Special Projects

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Join the Special Projects team at Apple as a Data Scientist specializing in synthetic data and ML evaluations, where you will work closely with Simulation and Machine Learning Evaluation teams to generate large multi-modal datasets for training and evaluating agentic AI models. Your day-to-day responsibilities include understanding model evaluation needs, analyzing discrepancies between simulated and real-world data, and collaborating on simulation performance improvements. Ideal candidates have a background in Computer Science or Data Science, at least two years of experience with large datasets, and proficiency in Python. Preferred qualifications include expertise in multimodal data handling, data-annotation pipelines, simulations for dataset production, experimental design, A/B testing, and strong cross-functional collaboration skills. This role involves tackling complex business problems related to conversational AI features that leverage advanced foundation models.

Skills

Python SQL TensorFlow PyTorch Keras Scikit-learn Pandas NumPy Jupyter AWS Google Cloud Platform Azure Git Docker CI/CD Prometheus Grafana Kubernetes Terraform

What you'll do

Design and generate large, multi-modal synthetic datasets for model evaluation.
Analyze discrepancies between simulated data and real-world data.
Evaluate and fine-tune the performance of agentic AI models on various tasks.
Translate subjective product requirements into objective criteria for analysis.
Prioritize and address gaps in simulation performance with the Simulation team.

What we're looking for

Bachelor’s or Master’s degree in Computer Science, Data Science, or related field
2+ years experience with large data sets and Python programming
Proficiency in managing multi-modal datasets and data annotation pipelines
Experience generating synthetic data for AI model evaluation
Strong statistical analysis skills and cross-functional collaboration abilities

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