AIML – Technical Process Engineer, Data Operations

Summary

Posted: Dec 30, 2024

Weekly Hours: 40

Role Number:200584877

Imagine what you could do here. At Apple, new ideas have a way of becoming extraordinary products, services, and customer experiences very quickly. Bring passion and dedication to your job, and there’s no telling what you could accomplish. The AIML Data Operations team is a fast paced, dynamic environment. In this role you will engage with teams across Apple’s ecosystem with the ultimate goal of delivering high-quality annotated data that meets their needs. You will leverage your technical expertise to support the design and optimization of data annotation processes for teams across Apple. Being successful as a Data Operations Process Engineer means that teams across Apple working on unreleased products and/or existing beloved features will come to rely on you to meet their annotation needs with high quality, efficient, and timely annotated data.

Description

You are a seasoned technical process and tools engineer with exceptionally high EQ, and you love working with people across technical and non-technical domains to solve problems and deliver results. In this role, you’ll have a chance to lean on all of your soft skills and technical background while you engage with teams across Apple’s ecosystem who are working on innovative machine learning technology. You will partner with operations and engineering teams to create tools that support data annotation and labeling projects. You will work closely with teams across Apple to build and refine tools that streamline data annotation workflows, ensuring high-quality, scalable, and efficient data pipelines. The ideal candidate will be comfortable working with SQL, Python, and other scripting languages to enhance tooling, as well as collaborating across teams to meet evolving needs.

Minimum Qualifications

• Develop and maintain tooling solutions that support efficient data annotation and labeling workflows.
• Automate and optimize annotation processes through custom scripts and automation frameworks (using SQL, Python, or other scripting languages).
• Partner with operations, engineering, and project management teams to understand annotation requirements and develop tools that meet specific project needs.
• Communicate with non-technical stakeholders to explain technical aspects of annotation tooling and incorporate feedback into tool design.
• Ensure that annotation tooling integrates seamlessly with data quality checks, improving data consistency and reducing errors during the annotation process.
• Modify and customize existing tools or scripts to adapt to changing requirements and optimize for scalability and performance.
• Continuously monitor the performance of annotation tools and workflows, identifying areas for improvement and implementing enhancements.
• Create and maintain clear, concise documentation for tools, processes, and workflows, ensuring ease of use for both technical and non-technical teams.
• Establish best practices for annotation tooling development and usage to ensure consistency across teams.
• Proactively identify risks or bottlenecks in the annotation tooling workflow and work to de-escalate or resolve issues.
• Troubleshoot and resolve issues with annotation tools, data pipelines, and automation processes to ensure minimal disruption to ongoing projects.

Preferred Qualifications

• Experience working with annotated data and ML researchers is a plus.