Senior ML Engineer, Siri User Experience Metrics and Data

Cupertino, CA - USA

Monthly Salary: Not Disclosed

Posted on: 30+ days ago

Vacancies: 1 Vacancy

Job Summary

Were looking for a Senior Machine Learning engineer with a proven record of building scalable statistical systems for business applications in a fast-paced this role you will drive the technical vision for Siris automated anomaly detection platform for detecting performance and reliability regressions. You are someone who is passionate about shipping quality code and continually improving our anomaly detection systems. You will be responsible for defining developing and delivering key features for high quality alerting to enable teams to troubleshoot regressions are someone who works extremely well across teams and organizations and demonstrates strong communication and technical leadership skills and the ability to engage with colleagues and leadership to find common ground on solving hard problems. You are someone who shares technical vision to leadership and engineering teams gathers feature requirements defines technical roadmaps and executes will be responsible for technically representing the team and communicating progress on key deliverables across the organization from peer groups to senior leadership. As the Senior ML engineer on the team you will be responsible for owning the technical roadmap onboarding and mentoring team members and leading the team to deliver high-impact are someone comfortable executing in a rapidly changing environment with ambiguous requirements to drive impact incrementally. You demonstrate strong problem solving skills and are self-directed with a proven ability to execute. You continually desire learning and demonstrate attention to details and find opportunities to innovate and share knowledge with others.

Masters degree with 8 years of industry experience in machine learning or Ph.D. with 5 years applying ML to real-world business problems.
Strong understanding of core ML concepts with particular depth in unsupervised learning methods (clustering dimensionality reduction density estimation) and a solid foundation in feature engineering model evaluation regularization and optimization.
Advanced coding skills in Python (5 years) with pandas scikit-learn and at least one deep learning framework (PyTorch or TensorFlow).
Hands-on experience data preprocessing building and training ML models using distributed processing frameworks such as PySpark Spark or Flink.
Experience applying large language models (LLMs) for downstream tasks (classification labeling enrichment) with the ability to perform fine-tuning or parameter-efficient adaptation (e.g. LoRA). Must be capable of deploying and optimizing models in on-premise server or on-device environments rather than relying solely on hosted third-party APIs
Demonstrated ability to set technical vision lead complex projects and drive impact in cross-functional environments with strong communication and problem-solving skills.

Proven expertise with anomaly detection and time series modeling (e.g. Isolation Forest autoencoders ARIMA LSTM) and experience building production frameworks supporting multiple engineering and product teams.
Experience with LLM workflows (domain adaptation RAG) and deploying optimized ML/LLM models on mobile or server environments (e.g. Core ML TensorFlow Lite ONNX Runtime) for performance cost and privacy.
Experience in developing ML infrastructure and large-scale operations including model serving distributed training CI/CD for ML pipelines and platform monitoring across millions of devices or events.
Familiarity with composite metrics and interpretability tools (e.g. SHAP LIME) with a track record of publications patents or open-source contributions in ML/LLMs anomaly detection or time series modeling.

Required Experience:

Senior IC

Masters degree with 8 years of industry experience in machine learning or Ph.D. with 5 years applying ML to real-world business problems.
Strong understanding of core ML concepts with particular depth in unsupervised learning methods (clustering dimensionality reduction density estimation) and a solid foundation in feature engineering model evaluation regularization and optimization.
Advanced coding skills in Python (5 years) with pandas scikit-learn and at least one deep learning framework (PyTorch or TensorFlow).
Hands-on experience data preprocessing building and training ML models using distributed processing frameworks such as PySpark Spark or Flink.
Experience applying large language models (LLMs) for downstream tasks (classification labeling enrichment) with the ability to perform fine-tuning or parameter-efficient adaptation (e.g. LoRA). Must be capable of deploying and optimizing models in on-premise server or on-device environments rather than relying solely on hosted third-party APIs
Demonstrated ability to set technical vision lead complex projects and drive impact in cross-functional environments with strong communication and problem-solving skills.

Proven expertise with anomaly detection and time series modeling (e.g. Isolation Forest autoencoders ARIMA LSTM) and experience building production frameworks supporting multiple engineering and product teams.
Experience with LLM workflows (domain adaptation RAG) and deploying optimized ML/LLM models on mobile or server environments (e.g. Core ML TensorFlow Lite ONNX Runtime) for performance cost and privacy.
Experience in developing ML infrastructure and large-scale operations including model serving distributed training CI/CD for ML pipelines and platform monitoring across millions of devices or events.
Familiarity with composite metrics and interpretability tools (e.g. SHAP LIME) with a track record of publications patents or open-source contributions in ML/LLMs anomaly detection or time series modeling.

Required Experience:

Senior IC

Key Skills

Computer Science
user experience
User Interface
SME
CSS
Interaction Design
Windows
Android
Usability Studies
Visual Design
HTML
User Research
JavaScript
Web Services
Wireframes

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About Company

Apple

Ask Siri to name the most successful company in the world and it might respond: Apple. And it's not just out of familial pride. Apple consistently ranks highly in profit, revenue, market capitalization, and consumer cachet. In 2018, the company became the first reach a trillion dollar ... View more

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