Edge-Driven ML Data Engineer: ML Ops & Cloud Pipelines

Applied Intuition; Sunnyvale (CA); On-site; USD 150,000 - 240,000; Full time

Job summary

Applied Intuition is building a data engine that runs ML models at the edge and ingests video data in the cloud for model iteration.

You will optimize data pipelines, evolve engine architecture for scalability, and integrate foundation models to automate labeling and quality assurance. This role collaborates with DoD stakeholders, enabling superior customer experiences during field events.

Qualifications

• 5+ years of relevant work experience.
• Familiarity with modern ML infrastructure, data-centric AI approaches and running large-scale jobs on GPUs.
• Created or worked on microservices and/or databases for data-oriented software.

Responsibilities

• Construct optimized data pipelines to run ML models.
• Evolve data engine architecture to scale labels, reduce annotation costs, accelerate ML iteration cycles.
• Integrate foundation models (LLMs, VLMs) to automate labeling, QA and data discovery.
• Leverage software-in-the-loop and hardware-in-the-loop testing.
• Interact with the DoD customer to understand use cases and triage needs.

Skills

ML infra

GPU workloads

Microservices

Data-oriented software

Tools

Docker

Kubernetes

OpenSearch

Postgres

Job description

Applied Intuition is building a data engine that runs ML models at the edge and ingests video data in the cloud for model iteration.

You will optimize data pipelines, evolve engine architecture for scalability, and integrate foundation models to automate labeling and quality assurance. This role collaborates with DoD stakeholders, enabling superior customer experiences during field events.