Member of Technical Staff, Contextual AI
Compute Infra
$140-300k
+ Equity
Office located in Mountain View, CA
Contextual language models for enterprise
Open for applications
Contextual language models for enterprise
21-100 employees
Open for applications
$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 degree in Computer Science, Engineering, or a related field (Ph.D. preferred)
- Experience: 5+ years of experience in building highly available, production-grade containerized distributed ML systems
- Technical Expertise: 5+ years of experience with ML infrastructure technologies such as Kubernetes, GCP, AWS, ArgoCD, Terraform, CloudFormation, infrastructure as code, containerization, SLURM automation, Linux fundamentals, GitHub Actions, and CI/CD
- Cloud Services: Demonstrated experience in managing cloud-based Kubernetes services
- Programming Skills: 5+ years of experience in one programming language such as Python, Java, or Go
- Machine Learning Knowledge: Familiarity with key concepts in machine learning, natural language processing, and computer vision
- Data Skills: Familiarity with data preprocessing, feature engineering, and data visualization
- HPC Experience: Familiarity with large GPU clusters and high-performance computing/networking
- Leadership: Experience in mentoring and growing junior engineers into successful leaders
- Communication: Excellent communication and collaboration skills, with the ability to work effectively in a fast-paced and dynamic environment
- If you are passionate about building and optimizing ML infrastructure to power cutting-edge AI solutions, we’d love to have you on our team
What the job involves
- As a Machine Learning Infrastructure Engineer, you will be responsible for building and maintaining the infrastructure that enables the development, deployment, and scaling of machine learning, data, and service pipelines
- You will collaborate closely with data scientists and full-stack developers to shape Contextual AI’s machine learning services and systems. Your role will be crucial in ensuring the scalability, reliability, availability, and performance of our RAG 2.0 systems
- Build and productionize ML infrastructure to support state-of-the-art RAG systems using technologies like Terraform, ArgoCD, Kubernetes, and cloud infrastructure providers
- Design, build, and optimize scalable machine learning infrastructure to support the training, evaluation, and deployment of large language models
- Instrument, monitor, and optimize the performance and reliability of Contextual AI’s services infrastructure
- Ensure security best practices are applied to application build pipelines and cloud/SaaS infrastructure
- Stay updated on the latest trends and best practices in MLOps, security, and AI to continuously optimize RAG infrastructures
- Work closely with stakeholders to understand business needs and translate them into technical solutions
- Mentor and guide junior AI engineers and team members, promoting technical excellence and knowledge sharing within the team
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
Insights
Few candidates hear
back within 2 weeks
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
Articles
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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