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Software Engineer - Generative Data Platform, Evaluation

Apple· Software and Services / AIML
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San Francisco, CA$150.4k - $225.3kfull-timePosted 3w ago

About the role

Software engineer on the Generative Data Platform evaluates and builds self-service tooling to generate synthetic data for ML models, enabling privacy-preserving training and evaluation, data quality assurance, and cross-team collaboration with ML engineers, data scientists, designers, and Safety/Responsible AI teams.

Responsibilities

  • Partner with ML engineers, data scientists, and designers to turn their needs into platform features.
  • Support teams as they build their own datasets on the platform, and help design model ablations that measure how synthetic data affects training and evaluation.
  • Explain how ML, vision, and generative models behave to people new to them, including cost, quality, speed, and feasibility.
  • Assess the domain gap between synthetic and real data, covering visual properties and non-visual ones such as metadata, value distributions, and labels.
  • Work with feature teams to find where synthetic data falls short for their use case, and build platform capabilities to close those gaps.
  • Help teams judge generated output, understand why results vary, and get closer to what they want.
  • Integrate new image and video generation models into a multi-stage production pipeline.
  • Operate and debug GPU workloads to keep generation reliable and cost-effective.

Qualifications

  • Bachelor's degree in Computer Science, Computer Engineering, or a related field, or 3 years of equivalent work experience.
  • 3+ years of experience building and operating production software in Python.
  • Experience debugging distributed systems or data pipelines in production, using logs, metrics, and task state to find root causes.
  • Experience deploying machine learning models on GPU infrastructure, including dependency management and GPU memory sizing.
  • Experience designing input validation and configuration contracts for systems where late failures are costly.
  • Demonstrated ability to explain machine learning concepts and tradeoffs to non-technical partners such as designers or product managers.
  • Proven, hands-on use of agentic AI coding tools in day-to-day software development, including judging where they are effective and where their output needs human verification.

Skills

Required:PythonDistributed systems / data pipelinesGPU infrastructure for MLInput validation / configuration contractsExplain ML concepts to non-technical partnersAgentic AI coding tools
Nice to have:Cross-functional collaborationGenerative image/video APIs

Benefits

  • Comprehensive medical and dental coverage
  • retirement benefits
  • range of discounted products and free services
  • reimbursement for certain educational expenses (tuition)
  • discretionary bonuses or commission payments (potential)
  • relocation assistance (potential)
  • Apple employee stock programs including RSUs and Employee Stock Purchase Plan
Last updated Oct 2, 2026. Interested? Apply on the company site.

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