Senior MLOps Engineer: Scalable Production ML Pipelines

Apple Inc.; Cupertino (CA); On-site; USD 216,000 - 325,000; Full time

Benefits offered by this job

Medical and dental coverage

Retirement benefits

Employee stock purchase plan

Job summary

Apple Inc. in Cupertino, California, seeks a Senior Machine Learning (MLOps) Engineer to build reliable, scalable ML infrastructure across the full lifecycle, bridging data science and engineering.

You will design automated pipelines for training, evaluation, versioning, and deployment, and champion observability, governance, and CI/CD practices to ensure production readiness. You will collaborate with ML engineers and data scientists to deliver impactful AI solutions and continuously improve

Qualifications

• 8 years in software engineering with large-scale systems
• Bachelor's degree in Software Engineering, Computer Science, Statistics, Data Mining, ML, OR
• Proven track record of shipping production-grade ML systems end-to-end
• Strong experience with distributed systems, databases (SQL/NoSQL), cloud platforms (AWS/Azure/GCP), and 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 CI/CD pipelines for ML workflows using Jenkins, GitHub Actions, or ArgoCD
• Strong understanding of data pipeline orchestration tools such as Airflow, Prefect, or similar

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

Skills

Python

CI/CD pipelines

Distributed systems

Education

Bachelor's degree in CS/SE/Stats/ML

Tools

Kubernetes

Ray

MLflow

Kubeflow

SageMaker

Vertex AI

GitHub Actions

ArgoCD

Airflow

Prefect

Job description

Apple Inc. in Cupertino, California, seeks a Senior Machine Learning (MLOps) Engineer to build reliable, scalable ML infrastructure across the full lifecycle, bridging data science and engineering.

You will design automated pipelines for training, evaluation, versioning, and deployment, and champion observability, governance, and CI/CD practices to ensure production readiness. You will collaborate with ML engineers and data scientists to deliver impactful AI solutions and continuously improve