Member of Technical Staff, Contextual AI

Full Stack

$160-250k

+Equity

React

AWS

TypeScript

GCP

JavaScript

Python

Azure

Junior and Mid level

San Francisco Bay Area

Office located in Mountain View, CA

Contextual language models for enterprise

Open for applications

Contextual language models for enterprise

21-100 employees

B2BArtificial IntelligenceEnterpriseDeep TechSaaS

Open for applications

$160-250k

+Equity

React

AWS

TypeScript

GCP

JavaScript

Python

Azure

Junior and Mid level

San Francisco Bay Area

Office located in Mountain View, CA

21-100 employees

B2BArtificial IntelligenceEnterpriseDeep TechSaaS

Company mission

To change the way the world works through AI.

Job

Company

Role

Who you are

Bachelor's degree or higher in Computer Science, Software Engineering, or a related field
2 years plus working experiences in full stack and backend development
Proficiency in programming languages such as Python, TypeScript/JavaScript, React
Experience with cloud platforms, such as AWS, Azure, or GCP, and familiarity with deploying applications on the cloud
Knowledge of machine learning concepts and frameworks is preferred but not a requirement
Excellent communication and interpersonal skills

What the job involves

As a Member of Technical Staff specializing in Full Stack Development, you will be responsible for designing, developing, and maintaining the application layer of our machine learning model provider platform
You will work closely with ML researchers, product managers, and designers to understand their requirements and translate them into scalable and efficient backend infrastructure and an intuitive frontend
Your expertise will be crucial in building a robust and user-friendly platform that enables our clients to leverage machine learning models effectively.What you'll do
Design and develop a scalable application layer, including both backend infrastructure and frontend components, from scratch
Collaborate closely with ML researchers, product managers, and designers to understand requirements and translate them into technical solutions
Implement secure authentication, authorization, and data protection mechanisms
Ensure seamless integration with machine learning models and pipelines, enabling efficient model deployment and management
Mentor and provide technical guidance to junior team members, promoting knowledge sharing and professional growth

Our take

Founded by former Facebook research scientists, Contextual AI is building customisable, scalable and trustworthy Large Language Models for use by enterprises. Its main product is a tool to improve model performance so that users can build production-grade AI systems.

The backbone of this product is a technology that feeds curated information into AI models so that the LLM can have more context and up-to-date information. This helps to minimise AI “hallucinations”, an increasingly common problem for models like ChatGPT.

Contextual AI is currently working with companies in the finance, technology and media sectors. Since its impressive 2024 funding, it will no doubt seek growth, perhaps into other sectors. Either way, as AI models become more and more common in enterprise use, the future looks bright for Contextual AI.

Freddie

Company Specialist at Welcome to the Jungle

Company

Funding (2 rounds)

Aug 2024

$80m

SERIES A

Jun 2023

$20m

SEED

Total funding: $100m

Company benefits

Nnovative Environment: Be part of a forward-thinking company that values creativity and innovation
Career Growth: Opportunities for professional development and career advancement
Collaborative Culture: Work with a talented and supportive team dedicated to excellence

Company HQ

SoMa, San Francisco, CA

Leadership

Douwe Kiela

(CEO)

Previously Adjunct Professor at Stanford University, Head of Research at Hugging Face and Research Scientist at Facebook. Was also the CEO and Founder of Brainstorm IT.

Amanpreet Singh

(CTO)

Previously Research Team Lead at Hugging Face, Research Engineer at Facebook AI, and Mobile Maintainer at jQuery Foundation. Was also a Software Engineering Intern at Amazon.

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