Staff AI/ML Platform Engineer
$114k - $228kAbbott
Abbott seeks a Staff AI/ML Platform Engineer to design and deploy machine learning infrastructure for the Lingo health platform. The role involves building production ML systems, connecting data pipelines to ML infrastructure, and enabling data science teams to deploy models safely across cloud and edge devices.
Responsibilities
- Define architecture and roadmap for AI platform, feature store, training pipelines, model registry, and deployment systems
- Partner with data engineering to define boundaries between curated data and ML features with full lineage tracking
- Extend CI/CD pipelines with model-specific stages including testing, validation gates, and approval workflows
- Implement model monitoring for performance, data drift, and sensor quality with alerting and rollback capabilities
- Build packaging and delivery pipeline for models to mobile and wearable devices with regulatory compliance
Requirements
- Bachelor's degree in Engineering, Mathematics, Computer Science, or related field
- Minimum 8 years software or ML engineering experience with 3+ years deploying models on mobile or embedded devices
- Hands-on experience with Azure ML SDK, Azure Data Factory, Databricks, MLflow, and Kubeflow
- Strong Python proficiency, knowledge of Docker and Kubernetes, infrastructure as code, and major cloud platforms
- Experience with data lakes, streaming or time-series data, and feature stores
- Proven implementation of model monitoring, drift detection, and automated retraining
- Experience partnering with DevOps and SRE teams on shared infrastructure
Compensation: $114,000–$228,000 base
$114k - $228k
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