AIML - Sr Machine Learning Engineer, Data and ML Innovation at Apple

Sunnyvale, California, United States -

Full Time

Start Date

Immediate

Expiry Date

11 Aug, 26

Salary

0.0

Posted On

13 May, 26

Experience

5 year(s) or above

Remote Job

Yes

Telecommute

Yes

Sponsor Visa

Skills

Machine Learning, Python, PyTorch, TensorFlow, JAX, Deep Learning, Multi-modal Models, Audio Processing, Foundation Models, Data Curation, Model Evaluation, Natural Language Processing, Computer Vision, Causality Analysis, Combinatorial Optimization, Generative AI

Industry

Computers and Electronics Manufacturing

Description

As part of Apple’s AI and Machine Learning org, we inspire and create groundbreaking technology for multi-modal models with strong agent and reasoning capabilities. The Data and Machine Learning Innovation (DMLI) team is seeking a passionate Machine Learning Engineer to explore new methods, challenge existing metrics and protocols, and develop new insightful practices that will change how we understand data and overcome real-world ML challenges. As a team member, you will work on some of the most ambitious technical challenges in the field. Your role will involve collaborating closely with our team of machine learning researchers, engineers, and data scientists. Together, you will spearhead groundbreaking research initiatives and develop transformative products designed to create a significant impact for billions of users worldwide. DESCRIPTION As a Machine Learning (ML) Engineer, you will be entrusted with the critical role of innovating and applying state-of-the-art research in foundation models to with a particular focus on audio data. This includes working across the full ML pipeline—from pre-training on large-scale unlabeled audio corpora to post-training evaluation and fine-tuning with task-specific datasets. The solutions you develop will have a significant impact on future Apple software and hardware products, as well as the broader ML ecosystem. Your responsibilities will extend to designing and developing a comprehensive multi-modal data generation and curation framework for foundation models at Apple. You will also contribute to building robust model evaluation pipelines that support continuous improvement and performance assessment. In addition, the role involves analyzing multi-modal data to better understand its influence on model behavior and outcomes. Furthermore, you will have the opportunity to showcase your groundbreaking research work by publishing and presenting at premier academic venues. MINIMUM QUALIFICATIONS Deep technical skills in one or more machine learning areas, such as computer vision, audio, combinatorial optimization, causality analysis, natural language processing, and deep learning. Strong software development skills with proficiency in Python; hands-on experience working with deep learning toolkits like PyTorch, TensorFlow, or JAX (one of). 5+ years of experience developing and evaluating ML applications, demonstrating a passion for understanding and improving model/data quality. B.S. degree or higher in Computer Science or related technical fields. PREFERRED QUALIFICATIONS Deep understanding of multi-modal foundation models. Staying up-to-date with emerging trends in generative AI and multi-modal LLMs. The ability to formulate machine learning problems, design, experiment, implement, and communicate solutions effectively. Hands-on mentality to own engineering projects from inception to shipping products and the ability to work independently and as part of a cross-functional team. Demonstrated publication records in relevant conferences (e.g., CVPR, ICCV, ECCV, NeurIPS, ICML, ICLR, etc.). Track records of adopting ML to solve cross-disciplinary problems.

Responsibilities

Innovate and apply state-of-the-art research in foundation models with a focus on audio data and multi-modal pipelines. Design data generation frameworks and build robust evaluation pipelines to improve model behavior and performance.