Description

Description

We're looking for a Senior Machine Learning engineer with a proven record of building scalable statistical systems for business applications in a fast-paced environment. In this role you will drive the technical vision for Siri's 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 rapidly. You 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 efficiently. You 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 outcomes. You 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.

Minimum Qualifications

• Master's 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.

Preferred Qualifications

• 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.

Pay & Benefits

At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $181,100 and $318,400, and your base pay will depend on your skills, qualifications, experience, and location.

Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses - including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.

Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant .