Member of Technical Staff, Contextual AI

Data Platform

$180-250k

+ Equity

Kubernetes

Python

Java

Elasticsearch

Terraform

Junior and Mid level

San Francisco Bay Area

Office located in Mountain View, CA

Context engineering platform for production-grade AI

Open for applications

Context engineering platform for production-grade AI

101-200 employees

B2BArtificial IntelligenceEnterpriseDeep TechSaaS

Open for applications

$180-250k

+ Equity

Kubernetes

Python

Java

Elasticsearch

Terraform

Junior and Mid level

San Francisco Bay Area

Office located in Mountain View, CA

101-200 employees

B2BArtificial IntelligenceEnterpriseDeep TechSaaS

Company mission

To change the way the world works through AI.

Job

Company

Role

Who you are

Education: At least a Bachelor's degree in Computer Science, Software Engineering, or related field
Experience: 2+ years in scaling Kubernetes services, distributed queuing systems, and streaming infrastructure. Proven ability to diagnose distributed vector databases and design systems for low-latency retrieval of image, text, audio, and video vectors
Technical Skills: 2+ years of experience with infrastructure tooling such as Terraform, Kubernetes, Python, Go, or Java
Machine Learning: Familiarity with machine learning concepts and frameworks, including dense information retrieval, document understanding/parsing models, and visual language models
Problem-Solving: Strong problem-solving skills and the ability to work effectively in a fast-paced, collaborative environment
Communication: Excellent communication and interpersonal skills, with the ability to work closely with cross-functional teams

What the job involves

The Data Platform team, within the Contextual AI platform organization, powers product development, applied research, and customers’ data-intensive workloads
The team designs, builds, and operates foundational data services at Contextual AI. This is a greenfield opportunity to shape the technical direction of the data engineering team at Contextual AI
Design and implement scalable services, APIs, and databases to support the processing and ingestion of petabytes of information daily
Architect and build streaming infrastructure, data orchestration systems, vector databases
Collaborate with ML researchers to understand state-of-the-art (SOTA) requirements for RAG systems, translating them into service specifications
Work directly with product managers and application engineers to understand customer requirements for end-to-end RAG systems, and translate them into technical solutions
Ensure seamless integration with machine learning models and pipelines, enabling efficient model deployment and management
Mentor and guide junior team members, promoting knowledge sharing and professional growth

Our take

Founded by former Facebook research scientists, Contextual AI is building customizable, 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 minimize AI “hallucinations”, an increasingly common problem for models like ChatGPT.

Contextual AI is currently working with companies in the finance, technology and media sectors. Following its 2024 funding round, the company has gained momentum, most recently announcing the launch of Agent Composer, a product aimed at moving enterprise RAG from experimentation to production ready AI agents.

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

Competitive salary & equity packages
Comprehensive health, dental & vision isnurance
401(k) with employer matching
Support for conference feeds & travel
Team offsites, celebrations & events
Unlimited PTO

Company HQ

Old Mountain View, Mountain View, CA

Leadership

Douwe Kiela

(Co-Founder & 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.

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