Coactive makes it easy to search, filter, and analyze visual content. Increasingly image and video data captures the content we watch, the products we buy, and the work we do, and already represents 80% of internet traffic. But rather than being an asset, visual content is often a tax or even a liability because it is so hard to work with and understand. Coactive solves this by bringing structure to unstructured visual data. Rather than spending months (or years) building complex infrastructure, data teams can unlock the value of their visual data in minutes to power use cases such as content understanding and moderation, search, and analytics.

Coactive was founded by experts who shaped the fields of high-performance deep learning and data-centric AI. We have the scars from building and working with the first generation of modern machine learning systems at Google, Meta, Pinterest, eBay, Lyft, and other leading organizations. Through our decades of experience, we have developed a playbook to democratize the toughest parts of machine learning systems; no PhD required.

This is an exceptional opportunity to work with one of Forbes' top 50 AI companies, backed by key investors such as Andreesen Horowitz and Bessemer Ventures. This position is truly a chance to be part of a category-defining team that is attracting top-tier talent interested in pushing the boundaries of what's possible in AI.

In Short

Design, build, and maintain highly scalable and reliable infrastructure on cloud platforms like AWS, GCP, and Azure.
Develop and optimize CI/CD pipelines to streamline deployment processes for microservices and data pipelines.
Manage and enhance real-time data workflows using technologies such as Kafka, Spark, and Databricks.
Implement robust monitoring and logging solutions to ensure system health and performance using tools like Datadog.
Establish and enforce cloud security best practices to ensure the integrity and safety of data and applications.
Automate infrastructure using tools like Terraform and orchestrate workloads with Kubernetes and related technologies.
Collaborate with ML and data engineering teams to create a seamless integration between infrastructure and data models.
Ensure efficient network setup and manage databases such as MongoDB, Postgres, and Redis.

Requirements

5+ years extensive experience in cloud infrastructure, particularly with AWS, and knowledge of GCP and Azure.
Hands-on expertise in Kubernetes, including deployment, scaling, and management, as well as related tools like Envoy and Keda.
Proficiency with data platforms and tools, including Kafka, Spark, and Databricks.
Strong Python programming skills for automation and infrastructure management.
Solid understanding of networking concepts and experience setting up and managing network infrastructure.
Experience with monitoring and logging tools, such as Datadog, to ensure observability and system reliability.
Proven experience with databases like MongoDB, Postgres, and Redis.
Ability to work independently in a fast-paced startup environment and solve complex problems with minimal guidance.

Benefits

Receive a monthly allowance to help cover prepaid medical services with the provider of your choice.
Connectivity Allowance – to help cover your internet and cellphone plans.