ML Data Engineer, Technical Lead – SIML, ISE

Key Skills

Aartificial intelligence, Apache Airflow, Data pipelines, Data Visualization, Design, Docker, Effective communication skills, ETL/ELT technologies, Kubeflow, Large data sets, Large Language Models - LLMs, Machine learning techniques, Natural Language Processing (NLP), Python Programming

Job Description

We’re looking for an exceptional engineering lead who is passionate about Apple products and values, who loves working with data ops at scale; and who is committed to the hard work necessary to continuously improve our ML data pipelines. We invite you to join us at this exciting time. Grow fast and positively impact multiple critical features on your first day at Apple!

Key Qualifications

• 8+ years of proven experience as a software engineer, with recent involvement in parts of the ML lifecycle
• 2+ years as a tech lead, specializing in data engineering/infrastructure
• Experience designing and building large scale data processing systems
• Consistent track record of managing complex data projects, while establishing and enforcing the right software engineering culture for a software team
• Experience in building data pipelines to process large scale datasets, using orchestration frameworks like Airflow, KubeFlow or other pipeline tools
• Demonstrated prior experience in large language models, or generative AI
• Expertise in Python or another modern programming language
• Strong ability to design and lead a technical roadmap, work with cross functional teams, with proven capacity to influence and build alignment
• Proven track record of mentoring and growing engineers, and establishing a strong software engineering culture

Description

In this position, you will be responsible for establishing and executing the strategy for our organization’s ML Data Engine, with an initial focus on agile ML Data OPs. This includes identification of infrastructure components and data stack to be used, design and implementation of pipelines between data systems and teams, automation workflows, data visualization and tools, data enrichment and monitoring tools. As a tech lead specialized in data engineering, you are expected to code and contribute to the stack. Our team of data engineers will use these systems to support end-to-end data flows tied to collection/annotation/QA operations, deliver high quality data quickly to ML teams, ensure traceability and versioning of data objects, and enforce compliance to contractual and regulatory obligations. You will work with SIML Data functions and with ML teams to assess data engineering needs tied to shipping ML features. You will partner with and influence the roadmap of teams that build infrastructure blocks that we rely upon (eg storage & labeling platforms), in order to contribute to a best-in-class ML Data Engine.

Education & Experience

Bachelors, Masters or PhD in Computer Science, Mathematics, Physics, or a related field; or equivalent practical experience.

Additional Requirements

• Strong understanding of applied machine learning topics
• Strong knowledge of either NLP or Computer Vision is desired
• Experience with ETL frameworks like Airflow is desired
• Kubernetes and Docker experience is desired
• Excellent written and verbal communication skills, ability to work efficiently with members of other data functions who are not engineers
• Self-starter, able to handle ambiguity, identify risks, troubleshoot, and find the right people and tools to get the job done

Pay & Benefits

• At Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $170,700 and $256,500, and your base pay will depend on your skills, qualifications, experience, and location.