Machine Learning - Data Scientist at Apple

Sunnyvale, California, United States -

Full Time

Start Date

Immediate

Expiry Date

29 Jul, 26

Salary

0.0

Posted On

30 Apr, 26

Experience

2 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Python, Machine Learning, Deep Learning, Computer Vision, LLM-as-a-Judge, Statistical Methodologies, Data Quality, NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow, Multimodal Models, Prompt Engineering, Failure Analysis, Benchmarking

Industry

Computers and Electronics Manufacturing

Description

Do you have a passion for computer vision and solving deep learning problems? The Video Engineering Data Analytics and Quality group is seeking an expert in evaluating machine learning and deep learning models, including foundation models and multimodal systems. This role will play a critical part in crafting robust evaluation frameworks, using both traditional statistical methods and modern techniques like LLM-as-a-Judge! The ideal candidate combines strong analytical thinking, expertise in Python, and advanced knowledge of statistical methodologies and data quality standards. This role involves collaboration with teams at Apple passionate about developing foundation models, including ML engineers, data scientists, and ML Infrastructure engineers to deliver amazing user experiences! DESCRIPTION Develop robust methodologies to assess the performance of foundation models (e.g., LLMs, vision-language models, etc.) across diverse tasks. Leverage LLMs as judges to perform subjective and open-ended model evaluations (e.g., for summarization, reasoning, or multimodal generation tasks). Build, curate, and lead evaluation datasets and benchmarks. Advanced proficiency in at least one scripting language, preferably Python. Collaborate with research, engineering, and product teams to define evaluation goals aligned with user experience and product quality. Conduct failure analysis and uncover edge cases to improve model robustness. Contribute to our tools and infrastructure to automate and scale evaluation processes. MINIMUM QUALIFICATIONS BS and a minimum of 3 years relevant industry experience Strong experience in evaluating supervised, unsupervised, and deep learning models. Hands-on experience evaluating LLMs and using them as scoring/judging mechanisms. Familiarity with multimodal models (e.g., image + text, video + audio) and related evaluation challenges. Proficiency in Python and libraries such as NumPy, pandas, scikit-learn, PyTorch, or TensorFlow. Solid understanding of statistical testing, sampling, confidence intervals, and metrics (e.g., precision/recall, BLEU, ROUGE, FID, etc.). Strong documentation skills, including the ability to write technical reports and present to non-technical audiences. PREFERRED QUALIFICATIONS Experience working with open-source evaluation tools like OpenEval, ELO-based ranking, or LLM-as-a-Judge frameworks. Familiarity with prompt engineering, few-shot or zero-shot evaluation techniques. Experience evaluating generative models (e.g., text generation, image generation). Prior contributions to ML benchmarks or public evaluations. Strong interpersonal skills.

Responsibilities

Develop and implement robust evaluation frameworks for foundation models, including LLMs and multimodal systems. Collaborate with cross-functional teams to define quality goals, conduct failure analysis, and automate evaluation processes.