ML Engineer

Apple, Inc.; Cork; On-site; EUR 90,000 - 130,000; Full time

Job summary

Apple's Software Localization & Release Engineering team seeks an ML Engineer to apply LLMs and machine learning to testing and releasing software for international users. You will collaborate with automation, quality, localization engineers, translators and project managers across multiple time zones to ship better software worldwide.

Responsibilities include building evaluation frameworks, reducing run costs and latency, designing adversarial grading, and developing datasets for model training

Qualifications

• Experience building production-grade ML applications using LLMs.
• Proficiency in prompt engineering and evaluating model performance.
• Strong coding skills in Python and Swift; backend ML services experience.

Responsibilities

• Build evaluation frameworks with benchmarks and graders to measure precision, recall and FPR.
• Reduce runtime costs and latency via prompts, models and design choices.
• Create feedback loops turning errors into better prompts and data.
• Design LLM-based systems for automated quality tasks and autonomous grading.
• Develop datasets for evaluation, training, or fine-tuning; maintain clean codebase.

Skills

LLM applications

Prompt engineering

Python

Swift

ML backend development

Tools

Open weights models

Local inference

CI/CD

Job description

Summary

Apple's Software Localization & Release Engineering team makes sure our software works well for people in every language and region. We're looking for an ML Engineer to apply LLMs and machine learning to how we test and release software for our international users.

Description

You’ll work alongside automation, quality and localization engineers, and with international quality engineers, translators and project managers across several time zones. Your work will help Apple ship better software to people around the world.

Responsibilities

• Your duties include:
• Build evaluation frameworks, including benchmarks, ground-truth datasets and graders. You'll measure precision, recall and false-positive rates, and drive them up.
• Reduce the cost and latency of each run through better prompts, better design and the right model for each stage.
• Build feedback loops that turn confirmed errors into better prompts, classifiers or training data.
• Designing and building LLM-based systems that carry out quality tasks and independently grade their own results, including adversarial grading approaches that catch false "pass" results.
• Designing classification pipelines that triage failures and separate real product issues from test or tooling problems.
• Building datasets to evaluate, train or fine-tune models.
• Writing clean, reviewable code, and helping the team keep a fast-moving codebase maintainable as it grows.

Minimum Qualifications

• Experience building production applications on top of LLMs, including tool use, structured output or agentic designs.
• Hands-on experience with prompt engineering and systematic model evaluation, such as writing rubrics or graders and measuring precision and false-positive rates.
• Strong programming skills in Swift / Python, and experience building backends for ML applications.
• Ability to improve model behavior iteratively, based on measured results.

Preferred Qualifications

• Hands-on experience fine-tuning or training models.
• Experience with computer vision or object detection, such as detecting elements in screenshots or documents.
• Experience with open-weights models and local inference.
• Experience with multi-agent systems.
• Familiarity with LLM serving infrastructure, such as model gateways, retries and cost-aware model selection.
• Experience building feedback loops that turn model failures into improved prompts, classifiers or training data.
• Familiarity with software test automation concepts, such as test execution, pass/fail grading and CI/CD.
• Experience in software localization or internationalization.
• Experience mentoring other engineers.

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Role Number: 200693662-1418