Agent Sciences and Infrastructure Engineer, AIML
Job Location:
Job Location:
Cupertino, CA - USA
Monthly Salary:
Not Disclosed
Monthly Salary:
Posted on:
4 hours ago
Posted on:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
The Apple Intelligence Agents Infrastructure and Research team brings innovative AI research into Apple products with a focus on optimizing interpreting and developing new algorithms for on-device and server-based Apple Foundation Models and Apple Intelligence features.
We are looking for talented engineers to build the infrastructure and agentic systems that are used to prototype optimize and ship Apple Intelligence features. You will join a collaborative team of software developers and applied scientists focused on large language modeling agent harnesses evaluation and the pipelines that connect training adaptation and deployment. Successful candidates will bring a strong software and systems engineering background hands-on experience building ML or agent infrastructure end to end and the judgment to make pragmatic tradeoffs between velocity and long-term maintainability.
Independently scope and lead complex multi-month engineering projects from an ambiguous starting point through to a production systemnProven ability to define goals and deliver results amid uncertainty and real-world constraints in AI product developmentnExperience designing building and operating infrastructure for machine learning - training/evaluation pipelines data and experiment tooling serving or agent harnessesnStrong software engineering fundamentals: distributed systems APIs testing and reliable maintainable codenStrong Python and UNIX skills and a demonstrated ability to use agentic coding tools in these environmentsnProven track record of driving engineering efforts to completion while overcoming obstacles and ambiguitynBS and 5 years of experience MS and 3 years of experience or PhD and 1 year of experience
Experience building agent frameworks tool-use systems or LLM evaluation infrastructurenExperience with data standardization validation and lineage for ML pipelines at scalenFamiliarity with post-training or optimizing large language models (LLMs) and the workflows around themnExperience shipping a real-world product project or featurenExperimental rigor and sound benchmarking/observability practices for complex systemsnAbility to reproduce and identify critical bottlenecks in the latest research and translate it into robust toolingnStrong communication and accountability skills with a collaborative mindset and strong work ethic
We are looking for talented engineers to build the infrastructure and agentic systems that are used to prototype optimize and ship Apple Intelligence features. You will join a collaborative team of software developers and applied scientists focused on large language modeling agent harnesses evaluation and the pipelines that connect training adaptation and deployment. Successful candidates will bring a strong software and systems engineering background hands-on experience building ML or agent infrastructure end to end and the judgment to make pragmatic tradeoffs between velocity and long-term maintainability.
Independently scope and lead complex multi-month engineering projects from an ambiguous starting point through to a production systemnProven ability to define goals and deliver results amid uncertainty and real-world constraints in AI product developmentnExperience designing building and operating infrastructure for machine learning - training/evaluation pipelines data and experiment tooling serving or agent harnessesnStrong software engineering fundamentals: distributed systems APIs testing and reliable maintainable codenStrong Python and UNIX skills and a demonstrated ability to use agentic coding tools in these environmentsnProven track record of driving engineering efforts to completion while overcoming obstacles and ambiguitynBS and 5 years of experience MS and 3 years of experience or PhD and 1 year of experience
Experience building agent frameworks tool-use systems or LLM evaluation infrastructurenExperience with data standardization validation and lineage for ML pipelines at scalenFamiliarity with post-training or optimizing large language models (LLMs) and the workflows around themnExperience shipping a real-world product project or featurenExperimental rigor and sound benchmarking/observability practices for complex systemsnAbility to reproduce and identify critical bottlenecks in the latest research and translate it into robust toolingnStrong communication and accountability skills with a collaborative mindset and strong work ethic
Required Experience:
Unclear Seniority
About Company
Ask Siri to name the most successful company in the world and it might respond: Apple. And it's not just out of familial pride. Apple consistently ranks highly in profit, revenue, market capitalization, and consumer cachet. In 2018, the company became the first reach a trillion dollar ... View more
