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Machine Learning Engineer, Data Solutions & Initiatives
Summary
Apple is a place where extraordinary people gather to do their best work. Together we craft products and experiences people once couldn’t have imagined — and now can’t imagine living without. If you’re excited by the idea of making a real impact, and joining a team where we pride ourselves in being one of the most diverse and inclusive companies in the world, a career with Apple might be your dream job! Apple is seeking a highly motivated and innovative Senior Machine Learning Engineer to join our worldwide sales team, Data Solutions & Initiatives (DSI). DSI is a product strategy and engineering team that works closely with business development and sales finance. In this position you will join a team of AI and ML Engineers focused on delivering ML and Generative AI agentic pipelines to move forward Apple’s critical financial planning and business activities.
DescriptionYou will be responsible for building a suite of AI / Machine Learning products that deliver measurable business value for Sales and Finance Business community working closely with Data Engineers, Software Engineers and MLOps. From requirement gathering to deployment and monitoring, passing by the design, the experimentation, the implementation and the testing; you will own the entire AI/ML pipelines to deliver best in class and highly available AI/ML systems.
Responsibilities- Partner with business stakeholders to clarify requirements, use cases and business metrics
- Collaborate with data engineers to establish data pipeline and prepare datasets for model building
- Work with software engineering to plan and execute the integration of the AI ML services
- Engage with business domain experts to understand data characteristics and create features for model training
- Design, build, evaluate and deploy ML models and AI agentic pipelines; monitor models performance and implement re-train strategies
- Collaborate with fellow AI/ML colleagues to develop reusable components that scale team delivery and improve maintainability
- Track, communicate, and explain the model impact to business stakeholders to drive adoption and demonstrate ROI
- Bachelor's degree in Computer Science, Machine Learning, or related technical field
- 5+ years of experience in Machine Learning Engineering, Software Engineering, or Data Science with focus on production ML systems
- Strong proficiency in Python and SQL
- Solid understanding of machine learning fundamentals including supervised and unsupervised learning algorithms
- Experience building and deploying ML models in production environments
- Familiarity with ML frameworks such as scikit-learn, PyTorch, OpenAI, Langchain/graph
- Strong software engineering skills with ability to write clean, maintainable code
- Experience with cloud platforms (AWS, GCP, or Azure) and basic cloud services
- Excellent problem-solving and analytical skills
- Strong written and verbal communication skills with ability to collaborate across technical and non-technical teams
- MS or PhD in Computer Science, Machine Learning, or related technical field
- 7+ years of Machine Learning Engineering, Software Engineering, Data Science or related roles with focus on production ML systems
- Track record with agentic workflows, advanced RAG architectures, and LLM frameworks (OpenAI, Anthropic, LangChain, LlamaIndex)
- Expertise in prompt engineering, fine-tuning, LLM evaluation, and vector databases (ElasticSearch, Chroma)
- Deep expertise in ML libraries (scikit-learn, PyTorch, XGBoost, LightGBM) and lifecycle management tools (MLflow, W&B)
- Experience with API frameworks (FastAPI, Flask) and monitoring tools (Grafana, Prometheus, LangFuse)
- Advanced AWS experience (EKS, S3, Athena, Lambda, SQS, EventBridge) and container orchestration (Kubernetes, Docker)
- Proficiency with workflow orchestration (Airflow), streaming technologies (Kafka, Kinesis), and caching solutions (Redis)
- Strong foundation in ML algorithms, transformer architectures, feature engineering, feature stores, and A/B testing
- Compiled languages (Go, Rust, Java, C++) with strong CI/CD and DevOps practices are a plus
- Ability to translate technical concepts for non-technical stakeholders and drive projects from conception to production
- Track record mentoring junior engineers with strong stakeholder management skills
Apple is an equal opportunity employer that is committed to inclusion and diversity, and thus we treat all applicants fairly and equally. Apple is committed to working with and providing reasonable accommodation to applicants with physical and mental disabilities.
