Machine Learning Software Engineer, Imbue

$140-350k

+ $10,000–$5,000,000 in equity

Python

PyTorch

Junior, Mid and Senior level

Remote in US

San Francisco Bay Area

Training AI in reasoning

Open for applications

Training AI in reasoning

21-100 employees

B2BArtificial IntelligenceDeep TechMachine LearningSaaS

Open for applications

$140-350k

+ $10,000–$5,000,000 in equity

Python

PyTorch

Junior, Mid and Senior level

Remote in US

San Francisco Bay Area

21-100 employees

B2BArtificial IntelligenceDeep TechMachine LearningSaaS

Company mission

To rekindle the dream of the personal computer—by creating practical AI agents that can accomplish larger goals and safely work for us in the real world.

Job

Company

Role

Who you are

Very comfortable writing Python
Familiar with PyTorch and training deep neural networks
Excited to work on open source code
Passionate about engineering best practices
Self-directed and independent
Excellent at getting things done

What the job involves

As a remote machine learning engineer, you’ll work very closely with a senior member of our research team on cutting-edge deep learning research, infrastructure, and tooling towards the goal of creating general human-like machine intelligence
Implement a self-supervised network using contrastive and reconstruction losses
Create a library on top of PyTorch to enable efficient network architecture search
Open source internal tools
Implement networks from newly published papers
Work on tools for simple distributed parallel training of deep neural networks
Develop more realistic simulations for training our agents
Design automated methods and tools to prevent common issues with neural network training (e.g. overfitting, vanishing gradients, dead ReLUs, etc)
Create visualizations to help us deeply understand what our networks learn and why

Our take

Since the widened attention placed on generative AIs such as Chat GPT, it seems that investors have intensified their interest in general intelligence. Imbue is one of the most recent AI research and training companies to step into the limelight after it achieved unicorn status in a $200 million Series B funding round in 2023.

With competition including the likes of OpenAI and Anthropic, Imbue researches and improves the reasoning of AI models. Its focus on foundational AI means that its training has a wide range of lucrative applications. Using a full-stack approach (essentially building its tech from scratch) enables the creation of feedback loops that gradually develop even better AI models.

Imbue’s approach indicates an evolving sector that is benefiting from increased funding. A newcomer to the unicorn stage, it’ll be interesting to see if the company can match up to its competitors now it has been bolstered by impressive funding.

Freddie

Company Specialist at Welcome to the Jungle

Insights

Led by a woman

Some candidates hear
back within 2 weeks

Company

Company benefits

Equity options
Yearly budget for self-improvement: coaching, courses, conferences, etc
Actively co-create and participate in a positive, intentional team culture
Spend time learning, reading papers, and deeply understanding prior work
Frequent team events, dinners, off-sites, and hanging out

Company values

We value in-person discourse, collaboration, and bonding
We treat people like creative agents, not fixed assets
We help you uncover and develop latent superpowers
We value freedom, autonomy, and self-direction
We provide context without adding to your todo list
We care about craftsmanship and quality code

Company HQ

SoMa, San Francisco, CA

Articles

Imbue raises $200 million at over $1 billion valuation in AI funding boost

Inside Nvidia's Aggressive Investment Strategy: Fueling the AI Revolution

Leadership

Kanjun Qiu

(CEO)

Current General Partner at Outset Capital and Sequoia Capital Scout. Previously CEO and Co-Founder at Sourceress and Member at South Park Commons.

Josh Albrecht

(CTO)

Current General Partner at Outset Capital. Previous CTO at Sourceress, Member at South Park Commons, and Public Data Lead at Addepar.

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