苹果Senior Software Engineer (MLOps)
任职要求
Minimum Qualifications • 6+ years of experience in the design and implement of Large-scale ML Systems or Distributed Systems • Experience with model pipeline and registry tools, detecting and preventing model drift, automating model monitoring and ensuring model accuracy • Proficiency in programming languages such as Python, Java or Golang • Effective communication skills in written and spoken English • Bachelor, or above in Software Engineering, Computer Science, Machine Learning, or a related field Preferred Qualifications • Experience in machine learning frameworks such as TensorFlow, PyTorch, AutoGluon, XGBoost or Scikit-learn • Experienced in DevOps Tools such as Docker, Jenkins, Ansible, Grafana, Prometheus, Elastic, or Kubernetes • Familiar with CI/CD deployment practices • Experience with SQL and database systems such as PostgreSQL • Experience with building ETL pipeline in data warehouse such as Snowflake • Experience with inference optimization
工作职责
This role requires a blend of skills in software engineering, machine learning, and operations to ensure the smooth functioning of ML systems in production environments. In this role you will: - Lead the team to design and implement automation for model training, testing, validation, and deployment - Collaborate with machine learning engineers to ensure efficient deployment and scaling of ML models - Implement monitoring and alerting systems to track model performance, system health, and data drift - Optimize compute resources for cost and performance efficiency - Manage model versions to ensure traceability and reproducibility
• Lead hands-on design and development efforts primarily using Python, building robust, scalable, and customer-focused AI/ML solutions. • Engage directly with key enterprise customers to strategize, architect and implement AI driven, Agentic AI solutions leveraging Azure AI services including Azure OpenAI, Azure ML. • Translate complex requirements into practical, well-architected technical solutions. • Develop end-to-end, rapid prototypes, involving data ingestion, validation, processing, and model deployment using Azure platform components. • Build, customize, and optimize AI models and related components for customer-specific use cases. • Integrate AI solutions with full-stack architectures, preferably leveraging experience with JavaScript frameworks (e.g., Node.js, React) and/or .NET ecosystems. • Establish and maintain robust CI/CD and ML Ops pipelines, leveraging Azure DevOps, Github for automated deployments. • Proactively explore diverse datasets to engineer novel features and signals that significantly enhance ML performance. • Participate actively in every phase of the model lifecycle from conceptualization, training, fine tuning, validation, and deployment, to continuous monitoring and improvement.
• Develop and optimize the control stack, including locomotion, manipulation, and whole-body control algorithms; • Deploy and evaluate neural network models in physics simulation and on real humanoid hardware; • Design and maintain teleoperation software for controlling humanoid robots with low latency and high precision; • Implement tools and processes for regular robot maintenance, diagnostics, and troubleshooting to ensure system reliability; • Monitor teleoperators at the lab and develop quality assurance workflows to ensure high-quality data collection; • Collaborate with researchers on model training, data processing, and MLOps lifecycle.
As a pivotal member of the Copilot Team, you will bring unique perspectives and expertise to the organization, driving innovative features and delivering transformative AI-powered experiences:• This is an IC role, Coding / engineering design time >70%• Manage complex projects from conception to implementation, with a focus on delivering AI-driven user interfaces and performance-optimized web applications.• Coordinate technical delivery through sprints, fostering collaboration throughout the project lifecycle.• Collaborate across geographies and time zones to establish best practices and develop automated processes that mitigate development risks.• Investigate and debug complex performance issues in applications, ensuring optimal user experience and system efficiency.• Design and implement performance testing strategies to proactively address bottlenecks.• Work closely with Product Designers, Product Managers, and Engineers to deliver AI-enhanced products that delight users.• Drive team-wide investments in infrastructure and foundational systems to support long-term technical roadmaps.• Solve technical challenges to deliver outstanding outcomes for customers and the business.
• Build, maintain, and enhance data ETL pipelines for processing large-scale data with low latency and high throughput to support Copilot operations.• Own data quality initiatives including monitoring, validation, and remediation to ensure integrity across attribution datasets and downstream dashboards.• Implement schema management solutions that enable quick and seamless evolution of attribution data without disrupting consumers.• Develop and maintain infrastructure that supports both batch and real-time attribution requirements.• Collaborate with product managers, marketing analysts, and data scientists to deliver insights for campaign optimization and growth strategies.• Design scalable attribution data architectures that can handle growing data volumes and evolving business needs.• Implement comprehensive monitoring and observability solutions for attribution pipelines, including SLA tracking and automated alerting.