Sr. Machine Learning Engineer, Foundation Models Inference - Cloud OS & Inference

Apple, Inc.; Paris; On-site; EUR 130,000 - 190,000; Full time

Job summary

Apple in Paris is seeking a Sr. Machine Learning Engineer focused on foundation models inference within Cloud OS & Inference. You will bridge research and production, optimize inference across language, vision, and speech, and shape the technical direction.

You'll own high-throughput, low-latency serving at planetary scale, mentor engineers, and collaborate with Foundation Model Research and security teams to deliver trusted, private AI workloads.

Qualifications

• Experience leading complex ML projects end to end.
• Proficiency in PyTorch or JAX and inference frameworks.
• Experience deploying models on cloud platforms with containerization.
• Strong knowledge of Transformers and multimodal architectures.
• Proven ability to ship production-grade inference systems.

Responsibilities

• Optimise inference for latest model architectures across language, vision and speech.
• Design and ship production-grade inference systems serving millions of users.
• Build profiling tools to identify and fix performance bottlenecks.
• Drive high-throughput, low-latency serving at scale and mentor engineers.
• Collaborate with Research and security teams on privacy and trust.

Skills

PyTorch or JAX

Python / Rust / Go

Cloud platforms (AWS, GCP)

Kubernetes & Docker

Inference frameworks

Lead ML projects

Transformers / multimodal

Education

MS in CS / ML / AI or related field

Tools

Kubernetes

Docker

TensorRT-LLM

vLLM

SGLang

TGI

Nvidia Triton Server

Job description

Sr. Machine Learning Engineer, Foundation Models Inference - Cloud OS & Inference

Paris, Ile-de-France, France Machine Learning and AI

We are the Foundation Model Inference team within Cloud OS and AI Inference organization. We are on a mission to build the most highly performant, secure and private inference stack that powers Siri AI, Apple Intelligence and Apps that are powered with the largest foundation models. Our systems serve billions of queries daily across Siri AI, Apple Intelligence, Apple Search, Apple Music, Apple TV, App Store, iMessage, Photos, Camera, Spotlight & Safari, at remarkably low latency with every ounce of compute extracted from the hardware beneath them. We optimise language, vision, and speech models with billions of parameters using state-of-the-art techniques and ship them at Apple scale. This is a rare opportunity to directly shape how AI reaches billions of people worldwide.

Description

You will work at the intersection of research and production, partnering closely with the Foundation Model Research team and our external partners to bring cutting‑edge model architectures from prototype to planetary-scale deployment. You will own hard problems in inference efficiency, hardware/software codesign, systems architecture, and tooling, and help set the technical direction for the engineers around you. This role sits within CloudOS and Private Cloud Compute (PCC) — Apple's purpose‑built, privacy‑preserving cloud infrastructure for AI workloads. PCC represents a first‑of‑its‑kind approach to running foundation models in the cloud with verifiable privacy guarantees, and CloudOS is the systems foundation that makes it possible. You will be building and optimising inference systems on top of this infrastructure, working closely with platform and security teams to deliver both performance and trust at scale.

Responsibilities

• Partner with the Foundation Model Research team and our external partners to optimise inference for the latest model architectures across language, vision, and speech.


• Design and ship production‑grade inference systems serving millions of customers in real time.


• Build profiling tools and simulators to identify and resolve performance bottlenecks across different hardware configurations and use cases.


• Drive technical decisions on high‑throughput, low‑latency serving at supercomputing scale.


• Mentor and grow engineers across the organisation.

Minimum Qualifications

• Experience leading complex ambiguous Machine learning projects end to end.


• Proficiency in PyTorch or JAX


• Experience working with Inference frameworks


• Experienced in Python / Rust / Go lang or similar programming languages


• Proficiency in deploying applications on cloud platforms (AWS, GCP or equivalent) using K8S and docker.

Preferred Qualifications

• Hands‑on experience with LLM inference stacks.


• Working knowledge of GPU or TPU programming concepts.


• Experience building and operating high‑throughput services at large distributed scale.


• Experience building productions systems in Go or Python.


• Strong knowledge of deep learning architectures including Transformers, encoder/decoder models, and multimodal variants.


• Experience with inference optimization frameworks such as TensorRT-LLM, vLLM, SGLang, TGI, or Nvidia Triton Server.


• MS in Computer Science, Machine Learning, Artificial Intelligence, Data Science, or a related field

At Apple, we're not all the same. And that's our greatest strength. We draw on the differences in who we are, what we've experienced, and how we think. Because to create products that serve everyone, we believe in including everyone. Therefore, we are committed to treating all applicants fairly and equally. We will work with applicants to make any reasonable accommodations.

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