Posted:3 days ago| Platform: Linkedin logo

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Full Time

Job Description

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About the Role

MLOps Engineer

Key Responsibilities

AWS-based cloud infrastructure

CI/CD pipelines

Docker, Kubernetes

container runtime environments

Support large-scale ML operations, including GPU-enabled workloads.

Python, Go, Bash, or Ruby

Infrastructure as Code (IaC)

Prometheus, Grafana, and the ELK stack

Elasticsearch, Kafka, HBase, and Spark

Collaborate closely with data scientists, engineers, and product teams to streamline deployment workflows.

Troubleshoot complex issues across the infrastructure, environment, and ML stack.

Required Qualifications & Skills

Computer Science

5+ years

AWS cloud services

Docker, Kubernetes

ML techniques

Python / Go / Bash / Ruby

Terraform, Terragrunt, Chef

Prometheus, Grafana, ELK stack

Elasticsearch, Kafka, HBase, Spark

Strong analytical, problem-solving, communication, and collaboration skills.

Why Join Us?

Remote-first

Opportunity to work on cutting-edge ML infrastructure.

Collaborative and growth-oriented team environment.

  • Freedom to innovate and implement your ideas.

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