Senior Machine Learning Engineer - Product Marketing

Position: Senior Machine Learning Engineer - Worldwide Product Marketing
Role Number:
Team:
Corporate Functions

Location:

Cupertino Weekly

Hours:

40

Posted:
Summary As a Machine Learning Engineer, you will design and build cutting-edge AI/ML systems that drive meaningful business outcomes  will work cross-functionally to bring innovative machine learning solutions from research and experimentation through to robust, production-grade deployment.

Description The MLE will collaborate with other MLEs to build scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment. This hire will design end-to-end AI/ML solutions with clear business impact, from concept to deployment, with a strong focus on feasibility, scalability, and performance. You will benchmark, adapt, and integrate AI/ML models into existing systems.

Minimum Qualifications 8 years of related experience building high-throughput, scalable applications or machine learning models in a production environment.

Bachelor's Degree in Computer Science, Statistics, Data Mining, Machine Learning, Operations Research, or related field.

Proficiency in one or more object-oriented programming languages such as Python, Java, or C++, with hands-on experience building distributed systems.

Experience building large-scale machine learning systems using big data technologies such as Spark, SQL, Snowflake, or similar platforms.

Experience with ML frameworks such as Tensor Flow, PyTorch, or scikit-learn.

Familiarity with MLOps practices including model versioning, CI/CD pipelines, and experiment tracking tools such as MLflow or similar.

Experience building and deploying applications using large language models (e.g., GPT-4, Claude, Gemini, or open-source alternatives) via APIs or self-hosted inference.

Hands-on experience with agentic frameworks such as Lang Chain, Llama Index, or Auto Gen to build multi-step, tool-augmented AI workflows.

Preferred Qualifications
10 years of related experience building high-throughput, scalable applications or machine learning models in a production environment.

Solid understanding of ML fundamentals including supervised/unsupervised learning, model evaluation, and feature engineering.

Strong problem-solving skills with the ability to translate ambiguous business problems into well-defined ML solutions.

Excellent cross-functional communication skills with the ability to collaborate effectively across engineering and data science teams.

Familiarity with LLM evaluation practices including output quality assessment, hallucination detection, and latency benchmarking in production environments.

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 $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…