Datatron Technologies

The Reliable AI Platform Built for the Enterprise

sf, silicon_valley, remote

11 - 25 Employees

11 - 25 Engineers

$2M - $5M Funding

Pre-Series A

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A cloud-native platform that operationalizes, monitors, and governs your AI and ML models. We enable enterprises to run mission-critical ML models in production while providing all necessary integration, monitoring and security requirements.

Active Roles

Principal Software Engineer San Francisco, CA, United States or Remote

QA Engineer Remote

Senior Frontend Engineer Remote

Senior Software Engineer (frond-end) San Francisco, CA, United States or Remote

Software Engineer (back-end) San Francisco, CA, United States or Remote

Why join us?

We are a technology company with a transparent and open culture powered by friendly-yet-ambitious designers and developers...empowered to evolve our products, automation and SDLC...while still getting the clear requirements and feedback necessary for your success.
Our leadership has experience creating successful, revenue-generating platforms, AI enablement infrastructure, and ML model-based services, at shops such as Twitter, Lyft, Snap, Oracle, VMWare, Citrix, Siemens, Google, Sling, Mastercard and Boeing.
Referenced by name in the 2021 Gartner Hype Cycle Report within the ML Ops category, as a high benefit in an emerging market.
We already have large enterprises from multiple industries currently using the software successfully, with the funding and appetite to rapidly grow new features and capabilities.

Engineering at Datatron Technologies

Engineering team and processes

We organize into small cross-functional pods of 4-5 people with different skill sets in user experience, software development, testing, and machine learning.

Our SDLC is dual-track agile where product designers and systems engineers drive the initial new ideas and epics, gather feedback, and identify specific feature set as a result. Features are prioritized for engineering sprints once readied by the first track, but each track and pod can work independently from the others.

All roles report into the Head of Engineering regardless of seniority level.

Technical Challenges

Our mission is to make our platform as agnostic as possible to the following for our customers:

The frameworks, dependencies, and runtimes required deploy and invoke their machine learning models
The infrastructure we can integrate with, whether security, identity, network, compute, or storage
The style of model algorithms utilized vs. the need to govern and monitor all models for certain key indicators and issues regardless of the algorithms

Tech stack

React

Python

Kubernetes

Flask

AWS

Hadoop

PostgreSQL

Scala