Machine Learning Engineer (MLOps), Evaluation
Job Location:
Job Location:
Cupertino, CA - USA
Monthly Salary:
Not Disclosed
Monthly Salary:
Posted on:
2 hours ago
Posted on:
Vacancies:
1 Vacancy
Vacancies:
Job Summary
We are seeking a highly experienced Machine Learning Engineer to build deploy and optimize Large Language Model (LLM)-based applications with a strong emphasis on MLOps/LLMOps (LLM operations) and scalable production systems. At Apple we believe in creating technology that enriches lives and empowers creativity. Youll play a pivotal role in developing Apple Intelligence driving the next generation of groundbreaking products across all Apple platforms.
The team is a growing group that works closely with product ML research Data Science and infrastructure teams to ensure the successful delivery of Apple Foundation models and Apple Intelligence evaluations. We are looking for a Machine Learning Engineer focusing on MLOps/LLMOps infrastructure to build a next generation LLM-powered evaluation this role you will be instrumental in scaling our internal evaluation platform building automation and self-service tools and ensuring the reliability and efficiency of large-scale LLM services. You will have the opportunity to create huge impacts across all AI products through innovations.
Explore design and implement advanced ML Infrastructure framework and standard methodologies for model integration deployment and monitoring using CI/CD LLM services are scalable efficient and secure for high-traffic LLM model observability incident response prompt versioning and feedback your ingenuity and creativity to resolve complicated and/or novel product and engineering challenImplement processes and frameworks for the continuous quality improvement of Apple Intelligence fostering excellence and closely with data scientists frontend engineers product managers and other stakeholders to define metrics gather requirements and deliver impactful solutions.
4 years in software engineering with experience in large-scale software system design and track record of shipping production-grade ML/LLM understanding of LLMs fine-tuning prompt engineering vector databases and RAG with distributed systems databases (SQL/NoSQL) cloud platforms (AWS Azure GCP) and container orchestration (Kubernetes).nAbility to tackle complex challenges think critically and deliver innovative communication skills and a team-oriented attitude thriving in a collaborative and fast-paced degree in Computer Science Engineering or a related field.
Hands-on experience with observability and evaluation tools for understanding of machine learning algorithms model evaluation metrics and data processing experience in a high-growth tech company or similar participation in open-source projects related to AI/ML or backend or Ph.D. in a related field.
The team is a growing group that works closely with product ML research Data Science and infrastructure teams to ensure the successful delivery of Apple Foundation models and Apple Intelligence evaluations. We are looking for a Machine Learning Engineer focusing on MLOps/LLMOps infrastructure to build a next generation LLM-powered evaluation this role you will be instrumental in scaling our internal evaluation platform building automation and self-service tools and ensuring the reliability and efficiency of large-scale LLM services. You will have the opportunity to create huge impacts across all AI products through innovations.
Explore design and implement advanced ML Infrastructure framework and standard methodologies for model integration deployment and monitoring using CI/CD LLM services are scalable efficient and secure for high-traffic LLM model observability incident response prompt versioning and feedback your ingenuity and creativity to resolve complicated and/or novel product and engineering challenImplement processes and frameworks for the continuous quality improvement of Apple Intelligence fostering excellence and closely with data scientists frontend engineers product managers and other stakeholders to define metrics gather requirements and deliver impactful solutions.
4 years in software engineering with experience in large-scale software system design and track record of shipping production-grade ML/LLM understanding of LLMs fine-tuning prompt engineering vector databases and RAG with distributed systems databases (SQL/NoSQL) cloud platforms (AWS Azure GCP) and container orchestration (Kubernetes).nAbility to tackle complex challenges think critically and deliver innovative communication skills and a team-oriented attitude thriving in a collaborative and fast-paced degree in Computer Science Engineering or a related field.
Hands-on experience with observability and evaluation tools for understanding of machine learning algorithms model evaluation metrics and data processing experience in a high-growth tech company or similar participation in open-source projects related to AI/ML or backend or Ph.D. in a related field.
Required Experience:
IC
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
