AIML - Sr Machine Learning Engineer, Evaluation

We are seeking a highly skilled and experienced machine learning engineer to join AIML Evaluation to build the systems that evaluate and refine Apple's foundation models and agents. As a key member of the team, you will help design and develop benchmarks, evaluators, simulation environments, and prompt and context optimization pipelines that drive quality improvements across Apple's AI experiences.

You will collaborate with product teams and the foundation model team to close the loop between observation and improvement, contributing datasets, environments, and reward signals that drive model and agent quality.

Description

Our team builds the benchmarks, environments, and tooling that power model and agent refinement, and turns observations into actionable opportunities for the next model and agent iteration. We work across the full spectrum of evaluation: offline benchmarks, device-in-the-loop simulation, and on-device observation in production. We develop LLM-as-judge evaluators, train reward models calibrated against human feedback, optimize prompts and context for agents, and contribute targeted datasets and reward signals to foundation model post-training.

In this role, you will play a crucial role in designing and developing evaluation and refinement infrastructure that supports a broad range of AI products at Apple.

You will work on agent and model evaluation across offline, device-in-the-loop, and on-device settings; build automated prompt and context optimization pipelines; and partner with product and research teams to translate failure analysis into measurable model and agent improvements.

You will also have the opportunity to engage with product teams across Apple and contribute to advancements in large language models and agentic systems that will reach millions of users.

To succeed in this role, you should have a strong background in machine learning systems, distributed infrastructure, and a proven track record of building and maintaining ML evaluation or training infrastructure.

You should be a proactive problem solver with excellent communication skills and the ability to work effectively across multiple codebases, teams, and organizations. Experience with LLM evaluation, reward modeling, prompt optimization, or agentic systems is highly desirable.

Responsibilities:

Your responsibilities will include: designing and building evaluation infrastructure for agents and foundation models; developing LLM judges, reward models, and prompt optimization pipelines; building and integrating simulation environments for agent evaluation and trajectory-based data generation; collaborating with product teams to identify, prioritize, and address quality gaps; and contributing datasets, environments, and reward signals to the foundation model post-training loop.

Preferred Qualifications

Experience with LLM evaluation, LLM-as-judge, or reward modeling

Experience with prompt optimization, agent harness development, or post-training (SFT, DPO, RLHF)

Proficiency in Python and ML frameworks such as PyTorch

Experience with agentic systems, simulation environments, or trajectory-based data generation

Familiarity with on-device or privacy-preserving ML

Proactive and determined problem-solving skills

Excellent communication skills

Minimum Qualifications

Strong background in machine learning and distributed systems

Experience building and maintaining ML infrastructure for evaluation, training, or deployment

Ability to work effectively across multiple codebases, teams, and organizations

8+ years of professional experience as a software engineer, preferably in machine learning or a related field

Bachelor's or Master's degree in Computer Science or a related field

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 $216,200 and $394,000, 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.