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AIML - Distinguished Engineer, Foundation Model

Apple· Machine Learning and AI
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Cupertino, CA$311.1k - $496.9kfull-timePosted 2w ago

About the role

Senior individual-contributor leadership role focused on setting technical direction for foundation model systems, starting with the inference engine used in training, evaluation, and model development. Lead across multiple teams to deliver a robust inference engine and extend impact into adjacent systems such as training infrastructure, data pipelines, and evaluation.

Responsibilities

  • Set and drive the technical vision and roadmap for the foundation model team's inference engine and the systems around it, used for training, evaluation, and LLM-as-judge workloads.
  • Lead deep work on inference performance, efficiency, and reliability: throughput and latency optimization, batching and scheduling, quantization, speculative decoding, KV-cache management, memory and compute efficiency, and hardware-aware optimization.
  • Architect inference systems that support a wide range of internal use cases - data generation and rollouts for training, offline and large-scale evaluation, and judge/reward scoring - across text, image, speech, and multi-modal models, each with distinct throughput, cost, and quality constraints.
  • Extend your impact into adjacent systems areas - training infrastructure, data pipelines, and evaluation harnesses.
  • Partner with many teams that depend on the engine, translating their diverse needs into a coherent platform, clear interfaces, and a prioritized roadmap.
  • Work closely with ML researchers and modeling teams to co-design models and systems, and to bring state-of-the-art techniques from prototype into the development loop reliably.
  • Lead a diverse set of engineers across teams in setting direction and executing against it; align stakeholders, resolve technical trade-offs, and make the calls that keep large efforts moving.
  • Drive prioritization and milestone delivery across competing demands, balancing near-term research needs against long-term platform investment.
  • Mentor and grow junior and senior engineers; establish engineering standards, review designs, and multiply the impact of the organization.

Qualifications

  • MS or PhD in Computer Science, Machine Learning, or related technical field, or equivalent industry experience.
  • 15+ years of experience building large-scale ML or distributed systems, with a track record of technical leadership and industry-wide or company-wide impact.
  • Deep, hands-on expertise in foundation model inference engines, with a proven record of improving performance, efficiency, and reliability at scale.
  • Deep experience supporting a diverse set of foundation model inference use cases, each with different throughput, latency, cost, and quality constraints.
  • Breadth beyond inference — the ability to contribute in adjacent systems areas such as training infrastructure, data systems, or evaluation.
  • Deep understanding of GPU/TPU/accelerator architecture, distributed systems, and model optimization (quantization, distillation, compilation, serving).
  • Proficiency with ML frameworks such as JAX, PyTorch, and with inference/serving stacks.
  • Proven experience leading a diverse set of engineers in setting vision and driving execution, including prioritization for milestone deliveries.
  • Demonstrated experience mentoring junior and senior engineers.
  • Demonstrated experience partnering with ML researchers and modeling teams to productionize research.

Skills

Required:Foundation model inference enginesPerformance optimizationDistributed systemsML frameworks (JAX, PyTorch)Leadership and mentorship

Benefits

  • Comprehensive medical and dental coverage
  • retirement benefits
  • range of discounted products and free services
  • education reimbursement for advancing your career including tuition
  • discretionary bonuses or commission payments (possible)
  • relocation assistance
  • employee stock purchase plan opportunities
  • Apple shareholder programs
Last updated Oct 23, 2026. Interested? Apply on the company site.

About Apple

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