Job Overview
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.
What you’ll do:
- Design, build, and maintain reliable and performant systems used across engineering.Work with your team to define technical strategy, architecture, and long-term goals.
- Collaborate with other engineers, product managers, and researchers to build infrastructure that meets evolving needs.
- Improve internal tooling, automation, and developer experience.
- Contribute to incident response, postmortems, and the development of best practices around system reliability and scalability.
- Distributed Systems: Owning and building important, highly scalable, available, performant, and reliable distributed systems (and their building blocks) to power the entire stack.
- Systems Engineering: Work across layers of the stack—debugging system bottlenecks, evolving core infrastructure, and solving novel problems in performance and scalability.
- Reliability Engineering: Build scalable, fault-tolerant systems and lead efforts around service health, incident response, and resilience.
- Observability: Design and maintain observability tooling (metrics, logs, tracing) to give teams visibility into production systems at scale.
- Developer Productivity: Create tools, environments, and workflows that help engineers ship high-quality software faster and more safely.
- Cloud Infrastructure: Own the cloud-native infrastructure (compute, networking, storage) that underpins all services and research workloads.
- Databases: Building high performance, distributed database systems that power all of Contextual’s product stack.
What we are seeking:
- Strong software engineering skills with experience in Python, or similar languages.
- Experience designing, operating, or scaling distributed systems or developer infrastructure.
- Comfort working in Linux environments, and with tools like Kubernetes, Terraform, CI/CD pipelines, and modern observability stacks.
- Ability to navigate complex systems and a willingness to dig deep when debugging tricky issues.
- Excellent communication and collaboration skills, especially in cross-functional settings.
Location: Mountain View, CASalary Range for California Based Applicants: $160,000 - $280,000 + equity + benefits (actual compensation will be determined based on experience, location, and other factors permitted by law).
Equal Opportunity
Contextual AI is an equal opportunity employer and complies with all applicable federal, state, and local fair employment practices laws. All qualified applicants will receive consideration for employment without regard to race, color, religion, national origin, ancestry, sex, sexual orientation, gender, gender expression, gender identity, genetic information or characteristics, physical or mental disability, marital/domestic partner status, age, military/veteran status, medical condition, or any other characteristic protected by law.
