AIML - Senior ML Research Engineer, AFM Safety

Join us as we build safe and reliable foundation models for Apple's products. Our team focuses on the research and methods needed to make large language models safe, fair, and robust at scale, with a current focus on agentic safety, model character and persona, and multimodal safety across audio and vision. We are looking for a researcher with a strong track record in applied ML who cares about safety and responsibility in foundation models. In this role, you will lead research and application of methods that keep Apple's foundation models safe while meeting Apple's standards for privacy and quality.

Description

This role works across many teams. You will work closely with ML researchers, engineers, and product teams to build and ship safety solutions for Apple's foundation models. The most useful research often comes from combining new methods with real product needs, and that is where we focus. As part of this role, you will:

* Define and deliver safety methods for foundation models, with emphasis on agentic safety, model character and persona, and multimodal safety (audio and vision)

* Research the safety and security risks of agentic systems, including tool use, and build the data and evaluations needed to address them

* Help define and safeguard the model's character and persona, so it behaves consistently and safely across contexts

* Build ways to train and evaluate foundation models with safety in mind, including for audio and vision modalities

* Research and improve safety alignment and robustness methods for large language models

* Work with engineers and researchers across teams to improve Apple products

* Partner with product teams to define requirements and drive quality and delivery

Preferred Qualifications

BS, MS, or PhD in Computer Science, Machine Learning, or a related field, or equivalent experience

Direct experience with LLMs and post-training methods, including safety alignment

Experience in one or more of: agentic safety (tool use, multi-step agents), model character and persona design, or multimodal safety (audio and vision)

Strong organizational skills and experience working across large, diverse teams

Minimum Qualifications

A strong ML background with hands-on experience training models, and a record of results shown through publications (e.g., ACL, CHI, CVPR, EMNLP, FAccT, ICML, Interspeech, NeurIPS, UIST) or other clear evidence of impact

Strong coding skills, including the ability to work with messy, real-world codebases

If not already experienced with LLMs, must be able to quickly pick up the skills needed for safety post-training

Strong collaboration and communication skills

Willingness to work with sensitive content, including exposure to offensive or controversial material

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 $184,700 and $324,800, 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.