
Machine Learning Engineer, Evaluation and Quality, Creativity Apps
San Diego, CAJobSeen 1 day agoSeen in employer's feed 1 day ago
Most applications go out cold — see where you stand first. No sign-up to start.
You apply on the employer's site, with no Olive account needed.
Watch jobs like this. New roles like this one near San Diego, CA, by email.
Don't just apply. Show up ready.
Olive works from this exact posting.
At a glance
Olive lists jobs from US employers, including remote roles you can work from the United States.
Job overview
The Machine Learning Engineer will own evaluation and quality for AI features across Apple’s Creativity Apps. The role defines evaluation strategies and metrics, builds representative datasets and scalable infrastructure, and drives quality from model development through shipping features. The engineer partners with machine learning, infrastructure, product, and design teams, and communicates evaluation results as ship/no-ship risks and recommendations.
Skills & qualifications
Skills
Qualifications
Full job description
Role Number: 200691707-7141
Summary
Imagine what you could do here. At Apple, new ideas have a way of becoming outstanding products, services, and customer experiences very quickly. Bring passion and dedication to your job and there's no telling what you could accomplish.
The Creativity Apps team is looking for a Machine Learning Engineer focused on the quality and evaluation of ML models and AI features in our creativity applications. You will define how we measure whether the product and AI features are good enough to ship: designing the evaluation strategy and metrics, building the datasets and infrastructure behind them, and driving end-to-end quality from model development through to the feature in customers' hands. You will have the unique and rewarding opportunity to help shape upcoming products that will delight and inspire millions of creators every day.
Description
In this role, you will own the evaluation and quality of AI features across Creativity Apps. You will work closely with Machine Learning engineering, infrastructure, product, and design teams to understand each model and use case, and translate them into evaluation methodology, testing strategy, and quality metrics that reflect what creators actually experience.
You will:
- Define evaluation strategy and metrics for ML models, LLMs, and AI features, tailored to the model, the product, and its use cases.
- Curate and create evaluation datasets, measure and improve dataset quality, and run iterative improvement loops so that datasets stay representative of each product.
- Design, build, maintain, and optimize evaluation infrastructure at scale, with reproducible runs, tracked baselines, and comparisons between model versions.
- Apply ML, LLMs, and agentic workflows to the evaluation itself, including automated judging, test generation, and analysis, to make evaluation more efficient, more accurate, and more scalable.
- Drive end-to-end evaluation and quality of AI features, from model checkpoints to integrated, shipping features, including triaging issues and driving them to resolution.
- Report quality clearly, turning evaluation results into ship/no-ship risk and recommendations for both technical and non-technical audiences.
- Partner with and drive cross-functional teams, comfortable with ambiguity and making educated, critical judgments.
Your curiosity about the latest developments in ML and generative AI, and your drive to apply new technology to practical problems, will set you apart.
Minimum Qualifications
-
5+ years of industry experience in machine learning or software engineering, with a focus on ML/AI model evaluation and quality.
-
Experience with evaluation methodology for ML models, LLMs, and AI products or features.
-
Strong understanding of the ML development cycle, from data and training to evaluation, deployment, and monitoring.
-
Solid machine learning fundamentals and LLM knowledge, including agentic workflows, and you keep up with the latest developments in the field.
-
Track record of applying LLMs, or agentic workflows to ML evaluation and quality.
-
Experience in data curation, dataset creation, and dataset quality, including iterative improvement workflows that deliver high-quality datasets tailored to specific products.
-
Experience designing, implementing, maintaining, or optimizing ML evaluation infrastructure at scale.
-
Experience designing evaluation metrics based on the model, the product, and its use cases.
-
Experience driving end-to-end evaluation and quality for AI products.
-
Fluency in quality reporting, presenting quality data to both technical and non-technical audiences.
-
Strong communication skills and experience working with and driving cross-functional partners.
-
Proficient in Python and/or Swift or comparable languages.
-
Bachelor's degree in Computer Science, Data Science, Machine Learning, or a related field, or equivalent experience.
Preferred Qualifications
-
Knowledge of the software development life cycle and software quality assurance methodologies.
-
Experience in objective image and video quality evaluation and metrics.
-
Knowledge of color science and/or experience with subjective image or video quality review.
-
Passion for creative applications; experience as a creator (photo, video, music, or design) is a plus.
-
Excitement about learning new technology and applying it to practical problems.
-
Familiarity with iOS and macOS.
Apple is an equal opportunity employer that is committed to inclusion and diversity. We seek to promote equal opportunity for all applicants without regard to race, color, religion, sex, sexual orientation, gender identity, national origin, disability, Veteran status, or other legally protected characteristics.
How this job compares
Set against the 6,278 open Machine Learning Engineer jobs on Olive Jobs, counted November 9, 2026.
- Pay
- This postingNot listed
- California median$180–263K/yr1,462 salary ranges
- California median$50–69/hr32 hourly ranges
- Openings
- Olive Jobs lists 1,939 open Machine Learning Engineer jobs in California and 6,278 across the US. 8% of them nationwide are listed as remote or flexible.
- Experience
- This posting asks for at least 5 years of experience; Machine Learning Engineer postings that state a minimum ask for 5 years at the median (4,993 postings).
- Education
- 2,037 of the 6,278 open Machine Learning Engineer jobs (32%) ask for a bachelor's degree or higher.
Counted across the open, public US postings on Olive Jobs on November 9, 2026. Pay medians are the middle values of the low ends and of the high ends of postings that list both ends of a range in the same cadence (a yearly salary or an hourly rate); a range's midpoint is halfway between its ends. Pay and experience figures resting on fewer than 20 postings are left out.
Prepare for this role
You've read the whole posting — now see how you match it.



