Staff Software Engineer
Apple
Staff Software Engineer
Job Description
Apple’s Data Platform powers the machine learning, AI, and data services that enable intelligent experiences across Apple products. As a Software Engineer focused on MLOps, you’ll help build the unified orchestration layer that powers large-scale data and ML workflows across the company. Leveraging cutting-edge open source technologies such as Ray and Spark, you’ll design and implement scalable systems that enable Apple teams to train models, analyze data, and deploy AI at Apple scale with strong governance. This is an opportunity to shape the future of ML infrastructure and have a direct impact on the experiences used by millions of people every day. As a Software Engineer on the Apple Data Platform team, you will design and develop orchestration systems that enable real-time, offline, and batch workflows for AI, ML, and data workloads across Apple. You’ll work with cross-functional partners and internal product teams to deliver reliable, scalable, and easy-to-use infrastructure that accelerates model development and deployment.
Locations
- Cupertino, California, United States 95014
Salary
Estimated Salary Rangemedium confidence
50,000,000 - 100,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- MLOpsintermediate
- machine learningintermediate
- AIintermediate
- data servicesintermediate
- orchestrationintermediate
- large-scale data workflowsintermediate
- ML workflowsintermediate
- Rayintermediate
- Sparkintermediate
- scalable systems designintermediate
- model trainingintermediate
- data analysisintermediate
- AI deploymentintermediate
- governanceintermediate
- ML infrastructureintermediate
- real-time workflowsintermediate
- offline workflowsintermediate
- batch workflowsintermediate
- cross-functional collaborationintermediate
Required Qualifications
- 5+ years of experience in MLOps, DevOps, or related infrastructure roles (experience, 5 years)
- Experience working in cross-functional teams and communicating technical concepts to diverse audiences (experience)
- Experience designing, building, and maintaining ML infrastructure and deployment pipelines using containerization technologies (Docker, Kubernetes preferred) and cloud platforms (AWS, Azure, or GCP) (experience)
- Proficient coding skills in Python, Go, or Scala with experience in ML frameworks (TensorFlow, PyTorch, MLflow, Kubeflow) (experience)
- Strong experience with Infrastructure as Code (Terraform, CloudFormation) and CI/CD tools (Jenkins, GitLab CI, GitHub Actions) (experience)
- Proficiency in monitoring and observability tools (Prometheus, Grafana, ELK stack) for ML model performance and system health (experience)
- Experience with data pipeline orchestration tools (Airflow, Prefect, Dagster) and streaming platforms (Kafka, Kinesis) (experience)
- Knowledge of ML model versioning, experiment tracking, and feature stores (MLflow, Weights & Biases, Feast) (experience)
- Experience with automated testing frameworks for ML systems, including data validation and model testing (experience)
- Understanding of security best practices for ML systems and data governance (experience)
- Excellent grasp of software engineering fundamentals and DevOps practices (experience)
- BS, MS in Computer Science, Software Engineering, Machine Learning, or equivalent degree with applicable experience (experience)
Preferred Qualifications
- Experience with React, NodeJS and ES6 concepts (experience)
- Experience with a modern front-end build tool, e.g. Webpack (experience)
- End-to-End Web application development experience. (experience)
- Good knowledge of APIs and REST architecture (experience)
- Proficient knowledge of Git and collaborative development workflows (experience)
Responsibilities
- As a Software Engineer on the Apple Data Platform team, you will design and develop orchestration systems that enable real-time, offline, and batch workflows for AI, ML, and data workloads across Apple. You’ll work with cross-functional partners and internal product teams to deliver reliable, scalable, and easy-to-use infrastructure that accelerates model development and deployment.
Tags & Categories
Staff Software Engineer
Apple
Staff Software Engineer
Job Description
Apple’s Data Platform powers the machine learning, AI, and data services that enable intelligent experiences across Apple products. As a Software Engineer focused on MLOps, you’ll help build the unified orchestration layer that powers large-scale data and ML workflows across the company. Leveraging cutting-edge open source technologies such as Ray and Spark, you’ll design and implement scalable systems that enable Apple teams to train models, analyze data, and deploy AI at Apple scale with strong governance. This is an opportunity to shape the future of ML infrastructure and have a direct impact on the experiences used by millions of people every day. As a Software Engineer on the Apple Data Platform team, you will design and develop orchestration systems that enable real-time, offline, and batch workflows for AI, ML, and data workloads across Apple. You’ll work with cross-functional partners and internal product teams to deliver reliable, scalable, and easy-to-use infrastructure that accelerates model development and deployment.
Locations
- Cupertino, California, United States 95014
Salary
Estimated Salary Rangemedium confidence
50,000,000 - 100,000,000 INR / yearly
Source: ai estimated
* This is an estimated range based on market data and may vary based on experience and qualifications.
Skills Required
- MLOpsintermediate
- machine learningintermediate
- AIintermediate
- data servicesintermediate
- orchestrationintermediate
- large-scale data workflowsintermediate
- ML workflowsintermediate
- Rayintermediate
- Sparkintermediate
- scalable systems designintermediate
- model trainingintermediate
- data analysisintermediate
- AI deploymentintermediate
- governanceintermediate
- ML infrastructureintermediate
- real-time workflowsintermediate
- offline workflowsintermediate
- batch workflowsintermediate
- cross-functional collaborationintermediate
Required Qualifications
- 5+ years of experience in MLOps, DevOps, or related infrastructure roles (experience, 5 years)
- Experience working in cross-functional teams and communicating technical concepts to diverse audiences (experience)
- Experience designing, building, and maintaining ML infrastructure and deployment pipelines using containerization technologies (Docker, Kubernetes preferred) and cloud platforms (AWS, Azure, or GCP) (experience)
- Proficient coding skills in Python, Go, or Scala with experience in ML frameworks (TensorFlow, PyTorch, MLflow, Kubeflow) (experience)
- Strong experience with Infrastructure as Code (Terraform, CloudFormation) and CI/CD tools (Jenkins, GitLab CI, GitHub Actions) (experience)
- Proficiency in monitoring and observability tools (Prometheus, Grafana, ELK stack) for ML model performance and system health (experience)
- Experience with data pipeline orchestration tools (Airflow, Prefect, Dagster) and streaming platforms (Kafka, Kinesis) (experience)
- Knowledge of ML model versioning, experiment tracking, and feature stores (MLflow, Weights & Biases, Feast) (experience)
- Experience with automated testing frameworks for ML systems, including data validation and model testing (experience)
- Understanding of security best practices for ML systems and data governance (experience)
- Excellent grasp of software engineering fundamentals and DevOps practices (experience)
- BS, MS in Computer Science, Software Engineering, Machine Learning, or equivalent degree with applicable experience (experience)
Preferred Qualifications
- Experience with React, NodeJS and ES6 concepts (experience)
- Experience with a modern front-end build tool, e.g. Webpack (experience)
- End-to-End Web application development experience. (experience)
- Good knowledge of APIs and REST architecture (experience)
- Proficient knowledge of Git and collaborative development workflows (experience)
Responsibilities
- As a Software Engineer on the Apple Data Platform team, you will design and develop orchestration systems that enable real-time, offline, and batch workflows for AI, ML, and data workloads across Apple. You’ll work with cross-functional partners and internal product teams to deliver reliable, scalable, and easy-to-use infrastructure that accelerates model development and deployment.
Tags & Categories