Platform Engineer - DevOps (3-5 yrs)

Job Title : Platform Engineer

Job Overview :

We are looking for an experienced Platform Engineer with expertise in DevOps, MLOps, and CI/CD pipelines to join our team with a minimum of 3 years of experience. This role involves building, maintaining, and optimizing the infrastructure and workflows that drive our development, deployment, and operational activities.

You'll play a key role in creating scalable systems to automate and support various engineering processes, empowering our development and data science teams to deliver high-quality, reliable products efficiently.

Key Responsibilities :

- Design, implement, and manage infrastructure to support cloud-native applications and machine learning models, ensuring high availability and scalability.

- Design and implement CI/CD pipelines to automate code deployment, testing, and release, ensuring a rapid and reliable release process.

- Develop and optimize MLOps frameworks to automate machine learning workflows from data ingestion, model training, deployment, and monitoring.

- Create automated solutions for repeatable processes, using scripts (i.e. , Python, Bash) and Infrastructure as Code (IaC) tools (i.e., Terraform, Ansible).

- Continuously evaluate and improve the automation of workflows to increase efficiency and minimize human intervention.

Required Qualifications :

- Education : Bachelor's degree in Computer Science, Engineering, or a related field (or equivalent experience).

- 3+ years of experience in a DevOps, Platform Engineering, or related role.

- Strong experience with CI/CD tools (i.e., Jenkins, GitLab CI/CD, CircleCI).

- Experience in MLOps, including tools like MLflow, Kubeflow, or DataRobot.

- Proficiency with cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes).

- Knowledge of Infrastructure as Code (IaC) tools, i.e., Terraform, Ansible.

Preferred Skills :

- Certifications in cloud platforms (e., AWS Certified DevOps Engineer, GCP Professional Cloud DevOps Engineer).

- Familiarity with data pipelines, data governance, and security in the context of MLOps.

- Experience with agile methodologies and collaboration tools like JIRA and Confluence