What you'll do:

• 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.

What we're seeking:

• Education: Master's or PhD degree in Computer Science, Software Engineering, or a related field.
• Experience: 2+ 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

If you are passionate about building scalable data infrastructure and working on cutting-edge AI solutions, we'd love to hear from you.

Location : Mountain View, CA

Salary Range for California Based Applicants: $180,000 - $250,000 + 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.