Senior Machine Learning Engineer

Apple • Seattle, WA

8h

About The Position

APPLE INC has the following available in Seattle, Washington. Research and develop advanced machine learning solutions for natural language processing (NLP), audio, computer vision, and multi-modal applications. Work closely with crossfunctional partners, including product teams, to productionize large-scale ML solutions. Provide technical guidance to improve workflows for training, evaluation, model optimization, and deployment. Contribute modular and performant Python code to internal PyTorch model development frameworks; develop, release, and support new features for these projects. Implement and maintain state-of-the-art neural networks architectures in internal frameworks. Architectures include large language models (LLMs), audio models, vision transformers, and multimodal generative AI models. Design, implement, and maintain production workflows for large-scale distributed training using advanced techniques such as fully sharded data parallelism and model parallelism. Implement and support tooling for evaluating the quality of large deep learning models. Research and evaluate the latest techniques for machine learning model development; incorporate them into production workflows. Contribute to the organization’s technical roadmap by identifying areas for innovation in machine learning solutions. Provide technical leadership to improve workflows for training, evaluation, model optimization, and deployment. Mentor and guide junior engineers and interns in best practices for machine learning model development. 40 hours/week. 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 $171,600 - $258,100/yr and your base pay will depend on your skills, qualifications, experience, and location. PAY & BENEFITS: 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: https://www.apple.com/careers/us/benefits.html. Note: Apple benefit, compensation and employee stock programs are subject to eligibility requirements and other terms of the applicable plan or program.

Requirements

• Master’s degree or foreign equivalent in Computer Science, Engineering, or related field and 3 years of experience in the job offered or related occupation.
• 2 years of experience with each of the following skills is required:
• Applying ML fundamentals to make quantifiable improvements to prior solutions in the domains of ML systems, natural language processing, computer vision, and/or audio processing
• Utilizing modern ML frameworks, including PyTorch or JAX, to train and evaluate generative AI models for natural language processing, computer vision, or audio applications.
• Applying software engineering fundamentals, with a strong focus on data structures and algorithms, to develop efficient and maintainable Python code for ML applications
• Using collaboration tools including git and GitHub to contribute to a large codebase with 3+ collaborators
• Experience and/or education must include:
• Implementing and maintaining tooling for industrial ML model development using Python and PyTorch or JAX
• Implementing state-of-the-art ML model architectures in PyTorch or JAX, including transformer models for text, vision, or audio applications
• Applying fundamentals of ML systems to scale up ML training to large models (at least 1 billion parameters) using fully sharded data parallelism (FSDP) or model parallelism
• Applying parameter efficient fine-tuning techniques, including LoRA (low-rank adaptation), to fine tune foundation models in a computationally efficient way
• Using distributed machine learning frameworks, including torch.distributed, DeepSpeed, or Ray, to build machine learning infrastructure or platforms
• Evaluating the quality of generative AI models using evaluation frameworks including lm-evaluation-harness

Nice To Haves

• N/A

Responsibilities

• Research and develop advanced machine learning solutions for natural language processing (NLP), audio, computer vision, and multi-modal applications.
• Work closely with crossfunctional partners, including product teams, to productionize large-scale ML solutions.
• Provide technical guidance to improve workflows for training, evaluation, model optimization, and deployment.
• Contribute modular and performant Python code to internal PyTorch model development frameworks; develop, release, and support new features for these projects.
• Implement and maintain state-of-the-art neural networks architectures in internal frameworks.
• Architectures include large language models (LLMs), audio models, vision transformers, and multimodal generative AI models.
• Design, implement, and maintain production workflows for large-scale distributed training using advanced techniques such as fully sharded data parallelism and model parallelism.
• Implement and support tooling for evaluating the quality of large deep learning models.
• Research and evaluate the latest techniques for machine learning model development; incorporate them into production workflows.
• Contribute to the organization’s technical roadmap by identifying areas for innovation in machine learning solutions.
• Provide technical leadership to improve workflows for training, evaluation, model optimization, and deployment.
• Mentor and guide junior engineers and interns in best practices for machine learning model development.

Benefits

• 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.
• Comprehensive medical and dental coverage
• Retirement benefits
• A range of discounted products and free services
• 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.

What This Job Offers

• Job Type: Full-time
• Career Level: Mid Level
• Number of Employees: 5,001-10,000 employees