Member of Technical Staff (Data Platform)

Contextual AIMountain View, CA
4d$180,000 - $250,000Onsite

About The Position

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.

Requirements

  • 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

Responsibilities

  • 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.

Benefits

  • equity
  • benefits
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