ML Data & Eval Engineer, Siri Agent Modeling

Apple • Cupertino, CA

15h

About The Position

The ML Data & Eval Engineer will build systems that support Siri on-device modeling, evaluation, and deployment. The role works closely with Siri modeling, evaluation, and deployment teams, as well as Apple’s ML platform, compute, framework, and privacy partners. It involves designing, building, and operating systems that turn data into trained, evaluated, and deployable on-device models. The engineer owns services and data products through conception, design, implementation, deployment, and maintenance, and may work across different parts of the ML lifecycle as priorities shift.

Requirements

• Strong computer science background in algorithms, data structures, and distributed systems design.
• Strong proficiency in Python.
• Hands-on experience with Docker, Kubernetes, and cloud infrastructure.
• Experience building large-scale data processing pipelines, such as with Spark or Ray, or distributed ML infrastructure.
• Familiarity with the ML model lifecycle, including training, evaluation, and deployment, and with frameworks such as PyTorch or JAX.
• Experience building, deploying, and debugging production services and data products end to end.
• Experience with agentic AI-assisted coding.

Nice To Haves

• Bachelor's degree in Computer Science, Engineering, or a related discipline, or equivalent industry experience.
• 4+ years of industry experience building production data or ML infrastructure.
• Experience building data pipelines for LLMs, such as synthetic data generation, LLM-as-judge filtering, or evaluation sets.
• Experience with workflow orchestrators such as Airflow, Kubeflow, or Argo.
• Experience with model conversion and optimization for on-device or edge deployment, such as Core ML, quantization, or pruning.
• Experience with data quality, lineage, and dataset versioning tools, and with privacy-preserving data practices.
• Experience building tools and services that optimize ML systems beyond model selection.
• Collaborative approach and experience driving large cross-team projects.

Responsibilities

• Design, build, and operate systems that turn data into trained, evaluated, and deployable on-device models.
• Own services and data products through conception, design, implementation, deployment, and maintenance.
• Work closely with Siri on-device modeling, evaluation, and deployment teams, and Apple's ML platform, compute, framework, and privacy partners.
• Contribute across the ML lifecycle, including data pipelines and training platforms, addressing major infrastructure bottlenecks.

What This Job Offers

• Job Type: Full-time
• Education Level: No Education Listed