Machine Learning Infrastructure Engineer

Our team designs and builds innovative and intelligent tools for our developers. You will be able to bring your experience in building and scaling backend systems to our unique problem domains. Your efforts will directly improve the machine learning workflow of both our team as well as a number of partner teams, whose scientists leverage our evaluation infrastructure to guide their experiments. You will be part of a data-driven team, analyzing the friction and cost associated with the scale at which we develop and ship complex software and systems. You will help design, build, and support large-scale model evaluation systems that support today’s models as well as tomorrow’s. You will collaborate closely with other developers to build a sophisticated solution, as well as stakeholders to understand requirements to help adopt your solutions and measure your impact. You will be most successful here as a flexible and proactive engineer who thrives in a supportive, respectful, and balanced work environment with interesting and challenging problems to tackle. You have excellent judgement and integrity with the ability to make timely and sound decisions. You know how to drive constructive technical discussions, learn from your team, and use your experience to advocate and teach others.In your role as a machine learning infrastructure engineer on our team you will:Spend most of your time working on data and machine learning systems.Develop proficiency with and knowledge of the Swift programming language and ecosystem.Collaborate with your teammates to help understand problems, define requirements and work with teams to implement long-lasting solutions.Engage with other teams to help identify issues and establish long-term relationships that include knowledge sharing.Provide valuable feedback loops to model training teams backed by data and metrics.Develop expertise and be given ownership over components critical to Apple’s success.Contribute to engineering a high-performance system through architectural design, algorithmic optimization, and performance tuning.Have access to the engineers who create Apple’s full technology, tools, and operating systems stack.Minimum Qualifications:3+ years of hands-on experience in building scalable backend systems for training and evaluation of machine learning/deep learning models.Understanding of machine learning, deep learning, natural language processing, distributed systems, reliability and scalability, containerization, and cloud platforms.Ability to efficiently develop, debug, and support new technologies in a changing environment.Strong problem-solving skills and ability to write production-quality clean code.Preferred Qualifications:Excellent collaborative skills, with strong written and verbal communication.Positive and respectful attitude in a diverse environment.Pay & Benefits:At 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 $170,700 and $256,500, 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.

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