Full-Time

Cloud Infrastructure Engineer

zaimler

zaimler

1-10 employees

AI readiness platform for enterprise data

No salary listed

Bengaluru, Karnataka, India

In Person

Category
DevOps & Infrastructure (1)
Required Skills
Kubernetes
Microsoft Azure
Python
Apache Spark
Apache Kafka
Infrastructure as Code (IaC)
AWS
Go
Terraform
Google Cloud Platform

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Requirements
  • 3–10+ years of engineering experience
  • Hands-on with Kubernetes and Terraform (real-world deployments)
  • Experience with distributed systems (Ray, Dask, Spark, or similar)
  • Exposure to Kafka or equivalent message queue systems
  • Strong programming and scripting in Python, Go, or similar
  • Track record of building or operating production-grade infrastructure
Responsibilities
  • Architect and scale infrastructure: Design and deploy secure, fault-tolerant cloud infrastructure across AWS, Azure, and Google Cloud Platform using Kubernetes, Terraform, and modern infrastructure as code tools
  • Enable distributed AI workloads: Build and optimize compute systems for distributed frameworks like Ray and Kafka, ensuring scalability and reliability
  • GPU orchestration: Manage GPU resources and scheduling for machine learning inference, retrieval, and training workloads
  • Drive observability and reliability: Implement monitoring, security, and best practices for high-availability ML/AI systems
  • Collaborate across teams: Work hand-in-hand with ML researchers and data scientists to ensure infrastructure accelerates development
Desired Qualifications
  • GPU scheduling/optimization experience
  • Prior startup/early-stage build-from-scratch experience
  • Experience supporting ML/AI workloads in production
  • Founder traits: excited to own infrastructure end-to-end as the first dedicated hire; comfortable with ambiguity; thrives in fast-moving, collaborative teams; curiosity and grit

Zaimler builds an enterprise data platform that makes data AI-ready by simplifying and organizing complex datasets for advanced applications. The platform ingests and structures data, automates taxonomy creation and knowledge-graph representations, and enables scalable preparation for machine learning and business intelligence. Led by veterans from LinkedIn, Meta, and Visa, Zaimler targets large-scale enterprises with an emphasis on AI readiness and scalable data infrastructure, backed by venture funding and early design partnerships. Its goal is to become the standard platform that lets large organizations unlock the value of their data through AI-ready infrastructure and scalable AI applications.

Company Size

1-10

Company Stage

N/A

Total Funding

N/A

Headquarters

N/A

Founded

N/A

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Simplify Jobs

Simplify's Take

What believers are saying

  • 2026 job posts claim active inbound prospects and proof-of-concept enterprise deals.
  • The 2025 ML Platform posting says Fortune 500 design partners already deploy the system.
  • LinkedIn updates in 2026 show Sofus Macskassy building a context platform for enterprise AI.

What critics are saying

  • Zaimler still looks stealthy in June 2024, so product-market fit remains unproven.
  • Hiring removed jobs in 2026 suggest churn, execution pressure, or fragile recruiting demand.
  • Openly targeting Fortune 500 insurance and travel invites Palantir, Databricks, and Snowflake competition.

What makes zaimler unique

  • Sofus Macskassy, ex-LinkedIn, brings knowledge-graph expertise built at production scale.
  • Zaimler sells semantic infrastructure for enterprise AI agents, not generic analytics software.
  • Their 2025-2026 jobs emphasize ontology automation, retrieval, and reasoning over fragmented enterprise data.

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Benefits

Health Insurance

Flexible PTO

Company Equity