About the role
AI summarisedApple is seeking a Senior Machine Learning Engineer to join the Data Solutions & Initiatives team within worldwide sales. The role involves designing, building, deploying, and monitoring end-to-end AI/ML pipelines, including generative AI agentic systems, to support financial planning and business operations. The engineer will collaborate with data, software, and MLOps teams to deliver measurable business value through production ML systems.
TechnologyOnsiteMachine Learning and AI
Key Responsibilities
- 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
- Owning the entire AI/ML pipelines to deliver best in class and highly available AI/ML systems
- Designing and implementing ML and Generative AI agentic pipelines
- Supporting Apple’s critical financial planning and business activities
- Collaborating with business development and sales finance teams
- Experimenting with and implementing advanced ML techniques
- Testing and monitoring deployed ML systems
- Ensuring high availability and reliability of AI/ML systems
Requirements
- 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)