Machine Learning Engineer, Agentic AI- Worldwide Product Marketing

About the job

As a Machine Learning Engineer, you will design and build AI/ML systems — from classical predictive models to LLM-powered agentic applications — that drive meaningful business outcomes at scale. You will take solutions from research and experimentation through to robust, production-grade deployment, with a growing focus on autonomous agents that reason, plan, use tools, and act on behalf of users and business processes. You will work cross-functionally to identify high-value agentic use cases and turn them into reliable, safe, and measurable products.

The MLOps Engineer will drive end-to-end quality initiatives across data ingestion, model training, deployment pipelines, and MLOps tooling. This hire will build, deploy, and optimize AI/ML based applications with a strong emphasis on scalable, and production-ready systems. You will establish standard methodologies for model integration, deployment, and monitoring using CI/CD principles.

Responsibilities

• Collaborate with other MLEs to build scalable, production-ready ML solutions, taking algorithms from initial concept through to deployment
• Design end-to-end AI/ML solutions with clear business impact, with a strong focus on feasibility, scalability, and performance
• Benchmark, adapt, and integrate ML and foundation models into existing systems
• Conduct rigorous model evaluation, testing, and iteration to continuously improve model quality and efficiency
• Design, build, and deploy LLM-powered agents and multi-agent systems that plan, reason over multiple steps, and complete complex business workflows with human-in-the-loop oversight
• Apply prompt and context engineering, structured outputs, and model routing to balance quality, latency, and cost across agent workflows
• Integrate classical ML models (e.g., forecasting, classification, ranking) as tools within agent workflows to ground agent decisions in quantitative predictions
• Deploy, monitor, and support agents and models in production with end-to-end tracing and observability (per-step traces, token usage, failure modes), feeding insights back into iteration
• Partner with data scientists, engineers, and business stakeholders to identify high-value agentic use cases and translate business requirements into technical ML solutions
• Contribute to shared ML and agent infrastructure, reusable components, tooling, and best practices across teams

Minimum Qualifications

• 4+ years of related experience building high-throughput, scalable applications or machine learning models in a production environment
• Proficiency in Python 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
• Solid understanding of ML fundamentals including supervised/unsupervised learning, model evaluation, and feature engineering
• Experience with ML frameworks such as PyTorch, TensorFlow, scikit-learn, or Hugging Face Transformers
• Experience building and deploying applications on large language models (e.g., Claude, GPT, Gemini, Llama, or other open-source models) via APIs or self-hosted inference (e.g., vLLM, TGI)
• Hands-on experience building agentic systems — tool/function calling, multi-step reasoning, memory, and RAG — with frameworks such as LangGraph, LangChain, LlamaIndex, AutoGen, or similar
• Experience evaluating LLM and agent outputs, including quality assessment, hallucination detection, task-success metrics, and latency benchmarking in production
• Strong problem-solving skills with the ability to translate ambiguous business problems into well-defined ML and agentic solutions
• Excellent cross-functional communication skills with the ability to collaborate effectively across engineering and data science teams

Preferred Qualifications

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

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 $277,600, 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.

EEO Statement

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. Learn more about your EEO rights as an applicant

Accessibility

At Apple, we believe accessibility is a fundamental human right. You’ll find that idea reflected in everything here — in our culture, our benefits and our digital tools. By welcoming as many perspectives as possible, we help you build a career where you feel like you belong.

Learn about accessibility in Apple’s workplace

Learn about reasonable accommodations for job applicants

Application Deadline

Apple accepts applications to this posting on an ongoing basis.