Sr. Machine Learning Engineer - ML Platform & Technology (MLPT)

$166,600 - $296,300/Yr

Apple - Seattle, WA

Full-time - Mid Level

Seattle, WA

Computer and Electronic Product Manufacturing

About the position

Join us in enabling the next generation of intelligent experiences in Apple's products and services with the latest advancements in Generative AI and Large Language Models! We are looking for a very experienced machine learning engineer who has also worked in ML infrastructure. Ideally, you should have experience with shipping intelligent features, end-to-end, and from idea to production. You should also have experience in building ML infrastructure to enable others to iterate faster and expertise in certain ML domains (preferably in Gen AI and LLM). You will help find novel solutions for our ML problems and collaborate with all ML teams at Apple to optimize our platform. Are you ready to impact billions of our users?

Responsibilities

• Be part of Apple's internal Machine Learning Platform group that enables ML teams to iterate their projects faster, from data engineering, labeling, training, online and offline evaluation, experimentation and more.
• Define and build the next set of features given the new challenges in the latest advancement of generative AI and large language models.
• Partner closely with customers and other internal partner ML teams across the company to help further adopt and apply our platform, gain feedback, and iterate our products (services, SDK, and web UI) to be more user-friendly and scalable.

Requirements

• A minimum of 3 years as tech lead.
• 8 years of proven experience in machine learning related software engineering, such as product, infrastructure, frameworks or tools.
• Strong expertise in machine learning domains, such as CV, NLP, recommender systems, Gen AI or LLMs (preferred).
• Proficient in ML training and deployment frameworks, like Tensorflow, PyTorch, Faster Transformer, TensorRT, vLLM.
• Proficient in cloud computing and data processing infrastructure and tools: Kubernetes, Ray, PySpark, SQL.
• Ability to clearly and concisely communicate technical and architectural problems, while working with partners to iteratively find solutions.

Benefits

• Comprehensive medical and dental coverage
• Retirement benefits
• A range of discounted products and free services
• Reimbursement for certain educational expenses, including tuition
• Discretionary bonuses or commission payments
• Relocation assistance
• Opportunity to participate in Apple's discretionary employee stock programs
• Eligibility for discretionary restricted stock unit awards
• Ability to purchase Apple stock at a discount through the Employee Stock Purchase Plan