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Senior Machine Learning Engineer- Worldwide Product Marketing

Apple· Corporate Functions
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Cupertino, CA$184.7k - $277.6kFull-timePosted 2w ago

About the role

MLOps Engineer focused on building and maintaining scalable, production-ready ML infrastructure. Responsible for end-to-end ML lifecycle, model deployment, observability, governance, and collaboration with ML Engineers and Data Scientists to deliver reliable AI/ML solutions.

Responsibilities

  • Explore, design, and implement advanced ML infrastructure frameworks and tools to accelerate model development and delivery.
  • Champion model observability, incident response, prompt versioning, and feedback loops to ensure continuous model health and performance.
  • Design and maintain automated pipelines for model training, evaluation, versioning, and deployment.
  • Partner closely with ML Engineers and Data Scientists to define metrics, gather requirements, and deliver impactful solutions.
  • Enforce model governance, validation standards, and best practices across teams to ensure reproducibility and compliance.
  • Identify and resolve bottlenecks in ML workflows, improving system reliability, latency, and throughput at scale.
  • Leverage AI coding assistants and LLM-based tools to accelerate development, automate repetitive tasks, and improve engineering productivity across ML workflows.
  • Use LLM-based tools to assist in drafting technical documentation, runbooks, and incident post-mortems, reducing operational overhead.
  • Apply LLM assistants to support code reviews, test generation, and pipeline debugging to improve overall code quality and team velocity.

Qualifications

  • 8 years in software engineering with demonstrated experience in large-scale software system design and implementation.
  • Bachelor's Degree in Software Engineering, Computer Science, Statistics, Data Mining, Machine Learning, Operations Research, or related field.
  • Proven track record of shipping and maintaining production-grade ML systems end-to-end.
  • Strong experience with distributed systems, databases (SQL/NoSQL), cloud platforms (AWS, Azure, or GCP), and container orchestration tools such as Kubernetes.
  • Hands-on experience with MLOps tooling and platforms such as Ray, MLflow, Kubeflow, SageMaker, Vertex AI, or similar.
  • Proficiency in Python and familiarity with ML frameworks such as TensorFlow, PyTorch, or scikit-learn.
  • Experience building and managing CI/CD pipelines for ML workflows using tools such as Jenkins, GitHub Actions, or ArgoCD.
  • Strong understanding of data pipeline orchestration tools such as Airflow, Prefect, or similar.

Skills

Required:ML infrastructure designModel observability and incident responseAutomated ML pipelinesCollaboration with data science teamsModel governance and validationMLOps toolsPythonML frameworksCI/CD for MLData pipeline orchestration

Benefits

  • Comprehensive medical and dental coverage
  • Retirement benefits
  • Discounted products and free services
  • Educational expense reimbursement including tuition
  • Potential discretionary bonuses or commission payments
  • Relocation assistance
Last updated Oct 9, 2026. Interested? Apply on the company site.

About Apple

Discover the innovative world of Apple and shop everything iPhone, iPad, Apple Watch, Mac, and Apple TV, plus explore accessories, entertainment, and expert device support.

Discover the innovative world of Apple and shop everything iPhone, iPad, Apple Watch, Mac, and Apple TV, plus explore accessories, entertainment, and expert device support.

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