Machine Learning Engineer - Strategic Data Solutions

$135,400 - $204,000/Yr

Apple - Seattle, WA

Full-time - Mid Level

Seattle, WA

Computer and Electronic Product Manufacturing

About the position

Imagine what you could do here. At Apple, new ideas have a way of becoming outstanding products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish. Apple's Strategic Data Solutions (SDS) team is looking for a hardworking individual who is passionate about crafting, implementing, and operating analytical solutions that have direct and measurable impact to Apple and its customers. As an SDS Machine Learning Engineer, you will employ predictive modeling and statistical analysis techniques to build end-to-end solutions for improving security, fraud prevention, and operational efficiency across the company, from manufacturing to fulfillment to apps and services. Apple's dedication to customer privacy, the adversarial nature of fraud, and the enormous scale of the business present exciting challenges to traditional machine learning and data science techniques. On this team, we will push the limits of existing data science methods while delivering tangible business value!

Responsibilities

• Engage with business teams to find opportunities, understand requirements, and translate those requirements into technical solutions.
• Design data science approach, applying tried-and-true techniques or developing custom algorithms as needed by the business problem.
• Collaborate with data engineers and platform architects to implement robust production real-time and batch decisioning solutions.
• Ensure operational and business metric health by monitoring production decision points.
• Investigate adversarial trends, identify behavior patterns, and respond with agile logic changes.
• Communicate results of analyses to business partners and executives.

Requirements

• Experience in machine learning and statistical analysis techniques.
• Proficiency in programming languages such as Python or R.
• Strong understanding of data structures and algorithms.
• Ability to work collaboratively with cross-functional teams.
• Experience with data engineering and platform architecture.

Nice-to-haves

• Familiarity with big data technologies such as Hadoop or Spark.
• Experience in fraud detection and prevention techniques.
• Knowledge of cloud computing platforms like AWS or Azure.

Benefits

• Comprehensive medical and dental coverage.
• Retirement benefits.
• Discounted products and free services.
• Reimbursement for certain educational expenses, including tuition.
• Discretionary bonuses or commission payments.
• Relocation assistance.