Staff / Principal Machine Learning Engineer, Inworld AI

$240-385k

+ Equity + Bonus

Python

C++

PyTorch

Senior and Expert level

San Francisco Bay Area

More information about location

1-3 days a week in office (Mountain View, CA)

AI-powered characters for virtual environments

Open for applications

AI-powered characters for virtual environments

101-200 employees

B2CB2BArtificial IntelligenceEnterpriseGamingDesignSaaSVirtual Reality

Open for applications

$240-385k

+ Equity + Bonus

Python

C++

PyTorch

Senior and Expert level

San Francisco Bay Area

More information about location

1-3 days a week in office (Mountain View, CA)

101-200 employees

B2CB2BArtificial IntelligenceEnterpriseGamingDesignSaaSVirtual Reality

Company mission

To transform static software into living AI systems that autonomously evolve to better serve their users.

Job

Company

Role

Who you are

A PhD in a relevant technical field, or a BA/BS degree with equivalent research and/or engineering experience
5+ years of combined experience in software development (Python, C++) and applied ML engineering
Demonstrated experience applying or researching ML in domains such as natural language processing, speech processing, and/or action planning
Strong foundation in data structures, algorithms, and neural network architectures
Proficiency with ML frameworks such as PyTorch

Desirable

A passion for learning and staying up-to-date with the latest advancements in ML research and its applications
Ability to work collaboratively in a fast-paced environment with shifting priorities
Familiarity with pre-training, fine-tuning, RLHF and evaluation of large language and speech models
Knowledge of working with embedded systems and/or running ML on edge devices
Strong background in mathematics and/or physics

What the job involves

We are seeking Staff and Principal level Machine Learning Engineers to solve these critical challenges
You will be responsible for researching, building, optimizing, and deploying the production ML systems that power our platform
Your work will focus on the difficult research and engineering problems of building the engine for the next generation of AI-driven software
Experiment with and implement cutting-edge ML models and techniques to advance our core AI capabilities
Train, evaluate, and optimize production-scale models and systems, focusing on quality, latency, cost, and on-device constraints
Collaborate with product and backend teams to translate novel ideas and research findings into robust, production-ready solutions

Our take

Dialogue writing for video games has traditionally been a matter of branching conversations based on player input, but this is a time-consuming and complicated process. In modern virtual environments which can contain thousands of characters, the need to save on costs means that conversations with many characters can be shallow and repetitive. Inworld AI's solution allows for the creation of unique and flexible interactions for even the most minor characters, based on just a few descriptive sentences.

Since launching, Inworld has quickly grown from an AI-character startup into one of the key players powering consumer AI. Its early work with companies like Xbox, Disney, and NBCUniversal helped provide the value of real-time AI experiences, and now a wide range of media companies, game studios, and fast-growing startups are building on its platform.

Now, with the recent release of Inworld Runtime, the company is taking an even bigger step. By opening up the internal system they originally built to handle huge, real-time consumer workloads, Inworld is positioning Runtime as the go-to backend for any team looking to scale from an idea to millions of users. Its adaptive graphs, automated MLOps, and one-click experiments remove most of the painful engineering work that usually slows teams now. And for Inworld, this turns Runtime into more than just a product, it becomes the core of the company's future.

Steph

Company Specialist at Welcome to the Jungle

Company

Funding (last 2 of 4 rounds)

Aug 2023

$50m

SERIES A

Aug 2022

$50m

SERIES A

Total funding: $117m

Company HQ

Mountain View, CA

Leadership

Ilya Gelfenbeyn

(Co-Founder & Executive Chairman)

Previously co-founded API.AI (now known as Google Dialogflow), a developer platform for building conversational experiences, and served as its CEO before Google acquired the company in 2016. The company also built Assistant.ai, the highest-rated independent voice assistant in the world with 40M+ users. Ilya was also the Founding Head of the Google Assistant Investments program at Google.

Michael Ermolenko

(Co-Founder & CTO)

Michael has extensive experience in leading AI teams and led Machine Learning Development at API.ai and the Dialogflow NLU/AI team at Google.

Kylan Gibbs

(Co-Founder & CEO)

Kylan has a background in turning advanced AI into products that naturally interact with humans. They came from DeepMind, where they led products for Conversational AI and Generative Models. Prior, Kylan worked on enterprise Machine Learning projects at Bain & Company.

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