Data Engineering Technical Lead, System Intelligent and Machine Learning - ISE
Location
Cupertino, CA | United States
Job description
Do you believe Machine Learning and AI can change the world? We truly believe it can! We are the Data Team of the System Intelligence and Machine Learning (SIML) group at Apple. We are responsible for building high quality ML datasets at scale, used to train ML models that power AI-centric features for many Apple products (iPhone, iPad, Mac, Apple Watch and even AirPods). Such features go from the smart wallpaper on your iPhone Lock Screen, to the models that highlight the faces of your loved ones in your Photos app, to input experiences (eg autocorrect, next word prediction, handwriting recognition).
We’re looking for an exceptional engineering leader 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 from your first day at Apple!
Key Qualifications
- 7 - 10+ years of industry experience as a software engineer, with recent involvement in parts of the ML lifecycle, and a strong understanding of applied machine learning topics
- Proven experience as a tech lead specializing in data engineering/infrastructure
- Experience designing and building large scale data processing systems; keeping up to date with the latest technologies, comfortable performing benchmarks, prototyping and bringing new systems to production
- The know-how to manage complex data projects while establishing and enhancing the right software engineering culture for our team
- Experience in building data pipelines to process large scale datasets, using orchestration frameworks like Airflow, KubeFlow or similar pipeline tools
- Expertise in Python, or another modern programming language
- Proficiency to design and lead a technical roadmap in alignment with R&D cross-functional teams with the capacity to influence other data infrastructure teams, and collaborate with members of our data Ops functions
- Self-starter, able to handle ambiguity, identify risks, troubleshoot, and find the right people and tools to get the job done
Description
In this position, 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. 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, versioning and lineage of data objects, and enforce compliance to contractual and regulatory obligations.
As a tech lead specialized in data engineering, you are also expected to code and contribute to the stack. You will establish and execute the strategy for our organization’s Machine Learning 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.
Education & Experience
Bachelors, Masters or PhD in Computer Science, Mathematics, Physics; or a related field, or equivalent practical experience.
Additional Requirements
- - Prior experience in large language models, or generative AI is desired
- - Experience mentoring and growing engineers
- - Solid understanding of either NLP or Computer Vision desired
- - Experience with ETL frameworks like Airflow is a plus
- - Kubernetes and Docker experience is a plus
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 $170,700.00 and $256,500.00, and your base pay will depend on your skills, qualifications, experience, and location. Apple employees also have the opportunity to become an Apple shareholder through participation in Apple’s discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple’s Employee Stock Purchase Plan. You’ll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits. Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program. Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.
In this position, 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. 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, versioning and lineage of data objects, and enforce compliance to contractual and regulatory obligations.
As a tech lead specialized in data engineering, you are also expected to code and contribute to the stack. You will establish and execute the strategy for our organization’s Machine Learning 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. Bachelors, Masters or PhD in Computer Science, Mathematics, Physics; or a related field, or equivalent practical experience.
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