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Member of Technical Staff, Backend - NomadicML

OodleSan FranciscoNomadicML
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Salary
Not listed
Job type
Full-time
Posted
28 Oct 2025
Status
Open · checked 7d ago

About this role

Frontdesk AI is seeking a Backend Member Technical Staff for the NomadicML department in San Francisco. This full-time position suits an infrastructure engineer who wants to build and scale the cloud systems behind cutting-edge video intelligence platforms.

Role Overview

NomadicML is hiring a Backend / Infrastructure Engineer to work at the intersection of cloud systems, SDK design, and large-scale inference infrastructure. The position involves building and scaling the backbone of the video intelligence platform, managing everything from secure cloud data ingestion to distributed GPU inference pipelines. Team members collaborate closely with machine learning researchers to productionize advanced foundation models, automate deployment and scaling, and deliver clean APIs and SDKs to enterprise clients worldwide.

Key Responsibilities

Architect GPU inference workflows to run massive multi-GPU inference jobs on foundation-scale video models while optimizing for throughput, cost, and reliability.
Build cloud upload infrastructure with direct integrations for AWS S3, GCP Storage, and Azure Blobs to support large-scale data ingestion via signed URLs and resumable uploads.
Design event-driven, autoscaling job systems using Kubernetes, Pub/Sub, or Ray to analyze terabytes of video data in parallel.
Develop developer SDKs and APIs, powering the Python SDK used for programmatic video ingestion, analysis, and search.
Construct end-to-end observability pipelines for logging, tracing, and metrics that track GPU utilization, job latency, and per-video inference health.
Support lightweight frontend integrations for the web application's cloud integrations and project workflows through backend endpoints and TypeScript SDK bindings.

Requirements

Deep proficiency in Python, Go, or TypeScript for backend systems.
Experience working with cloud platforms such as AWS, GCP, or Azure, including IAM, object storage, and compute APIs.
Strong understanding of GPU inference scaling, Kubernetes, container orchestration, and event-driven pipelines.
Prior experience designing REST or gRPC APIs, SDKs, or developer-facing infrastructure.
Familiarity with asynchronous job orchestration tools like Ray, Airflow, Dagster, or Temporal.
A practical mindset focused on transforming research-grade systems into reliable, fast, and usable products.

Nice to Have

Experience contributing to inference orchestration frameworks or machine learning infrastructure tools such as DeepSpeed, Triton, or Ray Serve.
Understanding of video encoding, chunking, and streaming formats for efficient multi-modal ingestion.
Basic front-end experience with React or Next.js for integrating backend pipelines into product workflows.
Background in machine learning infrastructure, observability, or data management systems.

Skills and Tools

Python, Go, TypeScript, React
AWS, GCP, Azure
Kubernetes, Ray, Airflow
Snowflake

About the Company

NomadicML is a department within Frontdesk AI, founded by Mustafa Bal and Varun Krishnan, who met while studying Computer Science at Harvard University. The leadership team brings deep expertise in distributed systems, large-scale model training infrastructure, and driver navigation AI models, with team members having built mission-critical AI systems at Snowflake, Lyft, Microsoft, Amazon, and IBM Research.

How to Apply

Interested candidates should visit the official company careers page to submit an application.

Skills and tech stack

Questions candidates ask

Where is this job located?

This full-time role is located in San Francisco, California.

What department is this position in?

This position is within the NomadicML department at Frontdesk AI.

What programming languages are required?

Candidates need deep proficiency in Python, Go, or TypeScript for backend systems.

What cloud platforms should applicants have experience with?

Applicants should have experience with AWS, GCP, or Azure.

How do I apply for this position?

You can apply by visiting the official company careers page.

Ready to apply?

The application is on the official Oodle careers page.

Apply on company site