Member of Technical Staff, Contextual AI
Platform
$140-300k
+ Equity
Office located in Mountain View, CA
Contextual language models for enterprise
Job no longer available
Contextual language models for enterprise
21-100 employees
Job no longer available
$140-300k
+ Equity
Office located in Mountain View, CA
21-100 employees
Company mission
To change the way the world works through AI.
Role
Who you are
- Education: Master’s or PhD degree in Computer Science, Software Engineering, or a related field
- Experience: 5+ years in scaling Kubernetes services, distributed queuing systems, and streaming infrastructure. Proven ability to diagnose distributed vector databases and Elasticsearch failures, and design systems for low-latency retrieval of image, text, audio, and video vectors
- Technical Skills: 5+ 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
- 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 Infrastructure 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, and Elasticsearch indices
- 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 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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