AIML - Senior Machine Learning Engineer, Computer Vision, Siri and Information Intelligence

$175,800 - $312,200/Yr

Apple - Cupertino, CA

Full-time - Senior

Cupertino, CA

Computer and Electronic Product Manufacturing

About the position

The Senior Machine Learning Engineer specializing in Computer Vision at Apple will play a crucial role in enhancing Siri's capabilities through advanced machine learning techniques. This position involves collaborating with multi-functional teams to implement and optimize computer vision models, ensuring high performance and scalability. The engineer will evaluate innovative algorithms and work with large datasets to improve the user experience of Siri, contributing to the future of AI systems and computing.

Responsibilities

• Evaluate and enhance computer vision capabilities of Siri's products.
• Collaborate with multi-functional teams to implement and optimize computer vision models.
• Conduct thorough evaluation and analysis of computer vision algorithms and models.
• Identify areas for improvement and optimization in existing models.
• Work with large amounts of real-world data to analyze and propose changes to the Siri user experience.
• Ensure data quality throughout all stages of acquisition and processing.
• Define and measure online and offline end-to-end metrics for deployed models.
• Run experiments and statistically interpret data with a focus on causation and data visualization.

Requirements

• 7+ years of professional work experience applying machine learning to real-world problems with a focus on computer vision.
• Excellent programming skills in Python.
• Experience with deep learning frameworks such as TensorFlow, PyTorch, or Keras.
• In-depth knowledge of computer vision algorithms and techniques, including image processing, feature extraction, and convolutional neural networks (CNNs).
• Experience working with large-scale datasets for training and evaluation of computer vision models.
• Excellent problem solving, critical thinking, and data analysis skills.
• Strong attention to detail.
• Proven track record to dive into data to discover hidden patterns and conduct error/deviation analysis.
• Effective communication skills and ability to collaborate effectively in a multi-functional team environment.

Nice-to-haves

• Strong background in A/B testing procedure, causal analysis, and cohort analysis.
• Exposure to model interpretability techniques and their real-world advantages/drawbacks.
• Good Conversational AI domain knowledge.
• Experience working with end-to-end pipelines and/or crowd-sourced data labeling.

Benefits

• Comprehensive medical and dental coverage
• Retirement benefits
• Discounted products and free services
• Reimbursement for certain educational expenses including tuition
• Discretionary bonuses or commission payments
• Relocation assistance