Machine Learning Ops Engineer, Applied Machine Learning

Machine Learning Ops Engineer, Applied Machine Learning
Company:

Apple Inc.


Details of the offer

Machine Learning Ops Engineer, Applied Machine LearningApple's Applied Machine Learning team has built systems for a number of large-scale data science applications. We work on many high-impact projects that serve various Apple lines of business. We use the latest in open source technology and as committers on some of these projects, we are pushing the envelope. Working with multiple lines of business we manage many streams of Apple-scale data. We bring it all together and unleash business value. We do all this with an exceptional group of software engineers, data scientists, DevOps engineers and managers. We are looking for a talented and dedicated engineer to join our team to bring passion for infrastructure and distributed systems, to build world-class platforms/products at a very large scale across cloud environments.
Description
Join Apple's Applied Machine Learning Team, as a Senior Software Engineer, to enable GenAI across our Applications & Platforms. Candidates should have a strong background in LLM core concepts, be proficient in setting up and supporting large scale big data applications in public cloud like AWS/GCP. The main responsibilities for this position include:
Build LLM Applications using open source LLM App Frameworks, AWS BedRock/GCP Vertex AIEvaluate and port Language Models onto optimized infrastructure to reduce cost and increase performanceBuild tools to benchmark and compare various embedding databases, LLMsBuild & Support CI/CD tools to port & manage applications on AWS/GCP & KubernetesBuild automation to enable self-healing systemsAbility to troubleshoot application specific, core network, system & performance issues.Build a multi-tenancy system by enforcing data protection between different use cases.Involvement in challenging and fast-paced projects supporting Apple's business by delivering innovative solutions.The candidate is expected to be self-motivated, proactive, and a solution-oriented individual.
Minimum Qualifications
Bachelors with 4+ years4+ years of experience in Python ProgrammingExtensive experience in deploying and managing applications on AWS/GCP & KubernetesDeep understanding of RAG based pipelines for Model inferencing, GuardRailsExperience in open source LLM App frameworks like LangChain/LlamaIndexPreferred Qualifications
BS in computer science with 4+ years or MS with 2+ years experience or related experience.Exposure to Cloud managed services like AWS BedRock/GCP Vertex AIGood Understanding of Agents in GenAIStrong Experience in Infrastructure templating tools like CloudFormation, TerraformExperience in GitOps based deployment tools like Spinnaker/Flux/ArgoCDStrong proficiency with Helm and Kustomize for managing Kubernetes applications and configurations.Experience in managing Embeddings using Vector databasesExposure to Promot engineeringExperience in observability & traceability for Large Language Models.Experience in Performance tuning on operating systems like LinuxExcellent analytical & problem-solving skillsExposure to various LLM infrastructure like GPUs, TPUs & Inferentia is preferredExposure to LLM runtime like Triton, Frameworks like TensorRT, vLLM is an added advantage.Exposure to general Java troubleshooting skillsAt Apple, base pay is one part of our total compensation package and is determined within a range. This provides the opportunity to progress as you grow and develop within a role. The base pay range for this role is between $175,800 and $312,200, and your base pay will depend on your skills, qualifications, experience, and location.
Apple employees also have the opportunity to become an Apple shareholder through participation in Apple's discretionary employee stock programs. Apple employees are eligible for discretionary restricted stock unit awards, and can purchase Apple stock at a discount if voluntarily participating in Apple's Employee Stock Purchase Plan. You'll also receive benefits including: Comprehensive medical and dental coverage, retirement benefits, a range of discounted products and free services, and for formal education related to advancing your career at Apple, reimbursement for certain educational expenses — including tuition. Additionally, this role might be eligible for discretionary bonuses or commission payments as well as relocation. Learn more about Apple Benefits.
Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We take affirmative action to ensure equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics. Learn more about your EEO rights as an applicant.

#J-18808-Ljbffr


Source: Jobleads

Requirements

Machine Learning Ops Engineer, Applied Machine Learning
Company:

Apple Inc.


Senior Data Infrastructure Engineer

At Webflow, our mission is to bring development superpowers to everyone. Webflow is the leading visual development platform for building powerful websites wi...


From Webflow - California

Published 9 days ago

Staff Backend Engineer

At Webflow, our mission is to bring development superpowers to everyone. Webflow is the leading visual development platform for building powerful websites wi...


From Webflow - California

Published 9 days ago

Senior Software Engineer, Analytics

At Webflow, our mission is to bring development superpowers to everyone. Webflow is the leading visual development platform for building powerful websites wi...


From Webflow - California

Published 9 days ago

Staff Data Infrastructure Engineer

At Webflow, our mission is to bring development superpowers to everyone. Webflow is the leading visual development platform for building powerful websites wi...


From Webflow - California

Published 9 days ago

Built at: 2024-10-05T12:26:04.236Z