AIML - Senior Machine Learning Engineer, NLP - Siri and Information Intelligence

$166,600 - $296,300/Yr

Apple - Seattle, WA

Full-time - Senior

Seattle, WA

Computer and Electronic Product Manufacturing

About the position

The Senior Machine Learning Engineer specializing in NLP/Conversational AI will play a crucial role in enhancing Apple Intelligence products, particularly within the Siri team. This position involves collaborating with cross-functional teams to implement and optimize machine learning models, ensuring high performance, accuracy, and scalability. The role focuses on evaluating state-of-the-art ML systems and improving the user experience of Siri through data analysis and model interpretability.

Responsibilities

• Evaluate and enhance Apple Intelligence products, focusing on NLP and Conversational AI.
• Collaborate with cross-functional teams to implement and optimize machine learning models.
• Conduct thorough evaluation and analysis of Apple Intelligence products and models.
• Ensure data quality throughout all stages of acquisition and processing.
• Define and measure online and offline end-to-end metrics for deployed models and predictors.
• Run experiments and statistically interpret data with a focus on causation and data visualization.
• Analyze large amounts of real-world data to propose changes to the Siri user experience.

Requirements

• 7+ years of professional work experience applying machine learning to real-world problems.
• Strong domain knowledge in NLP, conversational AI, or speech recognition.
• Excellent programming skills in Python.
• Strong data analytical skills and attention to detail.
• Proven ability to discover hidden patterns in data and conduct error/deviation analysis.

Nice-to-haves

• Strong background in A/B testing procedures, causal analysis, and cohort analysis.
• Exposure to model interpretability techniques and their real-world advantages/drawbacks.
• Good knowledge of Conversational AI.
• Experience with end-to-end pipelines and crowd-sourced data labeling.
• Experience with Big Data tools (MapReduce, Hadoop, Hive, Pig, Spark) for textual data analysis.
• Domain knowledge in applied statistics and experimental design.

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.