Generative AI Software Engineer
Apple
1 day ago
Full-time
On-site
Sydney, New South Wales, Australia
ML & AI Engineering
Imagine what you could do here! At Apple, new insights have a way of becoming extraordinary products, services, and customer experiences very quickly. Do you bring passion, dedication, and a strong eagerness to learn and innovate in the rapidly evolving field of Generative AI? If so, we are looking for individuals like you to join us in building groundbreaking experiences.
In this role, you will contribute to various stages of the Generative AI model lifecycle, from assisting with the creation and curation of diverse datasets to supporting the training, evaluation, and fine-tuning of generative models using Apple’s innovative ML tooling. You’ll collaborate cross-functionally with teams across Apple, helping to ensure seamless integration of these models into real-world products. You will also have opportunities to learn about and contribute to deploying generative models in production environments and building software solutions that enable workflows across the full software stack, driving innovative, user-focused experiences powered by advanced AI!
This is a full time role in our Employee Productivity and Support team to address and support continued growth in APAC and will present the opportunity to gain significant experience in a very large scale environment, while working with local experts to provide the highest level of service expected at Apple. We are looking for a self-driven individual who can constantly research and suggest latest technologies, independently troubleshoot technical issues, and work with teams of developers, engineering project managers, and test engineers who take pride in building AI solutions.
Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent practical experience. Strong proficiency in languages such as Python or Javascript. Familiarity with machine learning libraries like TensorFlow, PyTorch, Keras, or Hugging Face. Solid understanding of neural networks, deep learning, and specifically generative models Basic knowledge of Natural Language Processing (NLP) or Computer Vision (CV) concepts, depending on the primary modality of the generative models. Proficient in data manipulation tools such as Pandas, Numpy, and experience with data pre-processing techniques relevant to large and complex datasets. Experience with Git/GitHub for collaborative development. Strong analytical and problem-solving skills with a keen eye for detail. Ability to communicate technical concepts clearly and contribute effectively in a team environment.
Hands-on experience with large language models (LLMs) or other generative models, including tasks like prompt engineering, fine-tuning, or applying advanced metrics for analysis. Familiarity with specific generative model architectures (e.g. Transformer variants, Stable Diffusion, GPT-like models) and their underlying mechanisms (e.g. attention mechanisms). Understanding of software engineering best practices (e.g., testing, code reviews, modular design) in the context of ML systems. Comfortable presenting technical findings or research to peers and cross-functional global teams. Experience with data synthesis, augmentation, or specialised dataset preparation for generative tasks. Some familiarity with cloud platforms (e.g. AWS, GCP) for ML workload deployment. Demonstrated experience with personal, academic, or open-source projects involving Generative AI, showcasing practical application and problem-solving.
Description
This is a full time role in our Employee Productivity and Support team to address and support continued growth in APAC and will present the opportunity to gain significant experience in a very large scale environment, while working with local experts to provide the highest level of service expected at Apple. We are looking for a self-driven individual who can constantly research and suggest latest technologies, independently troubleshoot technical issues, and work with teams of developers, engineering project managers, and test engineers who take pride in building AI solutions.
Minimum Qualifications
Bachelor’s degree in Computer Science, Machine Learning, Artificial Intelligence, or a related technical field, or equivalent practical experience. Strong proficiency in languages such as Python or Javascript. Familiarity with machine learning libraries like TensorFlow, PyTorch, Keras, or Hugging Face. Solid understanding of neural networks, deep learning, and specifically generative models Basic knowledge of Natural Language Processing (NLP) or Computer Vision (CV) concepts, depending on the primary modality of the generative models. Proficient in data manipulation tools such as Pandas, Numpy, and experience with data pre-processing techniques relevant to large and complex datasets. Experience with Git/GitHub for collaborative development. Strong analytical and problem-solving skills with a keen eye for detail. Ability to communicate technical concepts clearly and contribute effectively in a team environment.
Preferred Qualifications
Hands-on experience with large language models (LLMs) or other generative models, including tasks like prompt engineering, fine-tuning, or applying advanced metrics for analysis. Familiarity with specific generative model architectures (e.g. Transformer variants, Stable Diffusion, GPT-like models) and their underlying mechanisms (e.g. attention mechanisms). Understanding of software engineering best practices (e.g., testing, code reviews, modular design) in the context of ML systems. Comfortable presenting technical findings or research to peers and cross-functional global teams. Experience with data synthesis, augmentation, or specialised dataset preparation for generative tasks. Some familiarity with cloud platforms (e.g. AWS, GCP) for ML workload deployment. Demonstrated experience with personal, academic, or open-source projects involving Generative AI, showcasing practical application and problem-solving.