AIML - Machine Learning Engineer, Data & ML Innovation
Apple Inc
Beijing, China
Job posting number: #7150487 (Ref:apl-200479192)
Posted: May 23, 2023
Application Deadline: Open Until Filled
Job Description
Summary
We are looking for machine learning engineers with a passion for solving cross-disciplinary challenges in hardware design and manufacturing scenarios. Be part of a highly accomplished, deeply technical and close-knit team of machine learning engineers, you will play a pivotal role in researching, developing, and implementing machine learning algorithms and models to solve complex real-world problems.
Key Qualifications
- Strong software development skills with proficiency in Python; Hands-on experience working with deep learning toolkits such as PyTorch or TensorFlow/JAX.
- Deep technical skills in one or more machine learning areas, e.g. computer vision, combinatorial optimization, commonality/causality analysis, deep learning.
- Ability to formulate a machine learning problem, design, experiment, implement and communicate solutions.
- Hands-on mentality to own engineering projects from inception to shipping product, and ability to work independently and as part of a cross-function team.
- Excellent interpersonal and communication skills, in both Mandarin Chinese and English.
- Passion for creating innovative techniques, making them robust and scalable, and realizing in high impact products.
Description
As a member of the AI/ML team, you will collaborate with teams across Apple, who are building the state-of-art, most compelling intelligent products in the world. You will also be a trusted advisor for best practice machine learning development. The process starts early in a product’s lifecycle as we explore what might be possible and identify challenges and their potential solutions, then continues as we rapidly iterate on collecting complex multimodal datasets, pulling out actionable insights, building algorithms/models, translating cross-functional insights into transformative prototypes, and finishing with detailed implementation and validation.
Your responsibilities include:
Conduct applied research to develop machine learning models and algorithms that address specific business challenges and objectives.
Collaborate with data scientists, software engineers, and cross-function domain experts to understand requirements and translate them into machine learning solutions.
Utilize cutting-edge techniques and frameworks in machine learning, deep learning, and statistical modeling to improve accuracy and efficiency.
Develop scalable and efficient machine learning pipelines, ensuring seamless integration into production systems.
Transferring machine learning solutions to data scientists and engineers in product teams; • Providing technical guidance to product teams on the choice of machine learning approaches appropriate for a task;
Stay up-to-date with the latest advancements and research in machine learning, actively participating in the research community.
Your responsibilities include:
Conduct applied research to develop machine learning models and algorithms that address specific business challenges and objectives.
Collaborate with data scientists, software engineers, and cross-function domain experts to understand requirements and translate them into machine learning solutions.
Utilize cutting-edge techniques and frameworks in machine learning, deep learning, and statistical modeling to improve accuracy and efficiency.
Develop scalable and efficient machine learning pipelines, ensuring seamless integration into production systems.
Transferring machine learning solutions to data scientists and engineers in product teams; • Providing technical guidance to product teams on the choice of machine learning approaches appropriate for a task;
Stay up-to-date with the latest advancements and research in machine learning, actively participating in the research community.
Education & Experience
Master or PhD in Machine Learning, Computer Science, Mathematics, Physics, or related technical field, with 2+ years of experience in machine learning research or development.
Additional Requirements
- Having one or more qualifications below is a plus
- Experience with large language models and proficiency in fine-tuning and adapting large language models for ML tasks.
- Familiarity with foundation models, which serve as the basis for various language-related tasks and can be fine-tuned for specific applications.
- Expertise in multi-modal modeling, incorporating multiple modalities (text, images, audio, etc.) to create comprehensive models for tasks such as image captioning, visual question answering, or multi-modal sentiment analysis.
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