Machine Learning Infrastructure Engineer

$175,800 - $264,200/Yr

Apple - Cupertino, CA

Full-time - Mid Level

Cupertino, CA

Computer and Electronic Product Manufacturing

About the position

Our team is on a mission to bring the latest machine learning techniques to the field of software development. We want to make it easier for our developers to write, build, and test their code. We firmly believe that providing better, more intelligent tools and infrastructure to our developers will help unlock their creativity and innovation, which Apple's customers will experience in our products. We are looking for tools and infrastructure developers to join us in our efforts. As part of our team, you will be developing novel machine learning tools and frameworks focused on scalable evaluation of generative models. This work will touch on all stages of the code lifecycle: coding, testing, building, and deployment. If you are a software engineer, with a passion for machine learning, who enjoys building new systems and adapting them to a rapidly evolving field, then we have many exciting problems for you to work on! You will join a tight-knit team of research scientists and engineers to tackle technical and human-centered challenges and have fun while doing so. 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.

Responsibilities

• Develop novel machine learning tools and frameworks focused on scalable evaluation of generative models.
• Work on data and machine learning systems.
• Develop proficiency with and knowledge of the Swift programming language and ecosystem.
• Collaborate with teammates to understand problems, define requirements, and implement long-lasting solutions.
• Engage with other teams to 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 ownership over components critical to Apple's success.
• Contribute to engineering a high-performance system through architectural design, algorithmic optimization, and performance tuning.

Requirements

• 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.

Nice-to-haves

• Excellent collaborative skills, with strong written and verbal communication.
• Positive and respectful attitude in a diverse environment.

Benefits

• Comprehensive medical and dental coverage
• Retirement benefits
• Discounted products and free services
• Reimbursement for certain educational expenses, including tuition
• Discretionary bonuses or commission payments
• Relocation assistance
• Opportunity to participate in Apple's discretionary employee stock programs
• Ability to purchase Apple stock at a discount through the Employee Stock Purchase Plan