Description

You will lead and advance the internal Data Science and AI/ML platform strategy, building MLOps platforms and Gen AI solutions on GCP. You will collaborate with engineers, product managers, and data scientists to deliver reusable AI/ML components and drive iterative releases.

This role is on-site.

Responsibilities

• Develop and maintain MLOps platforms and Gen AI solutions on GCP using Python for data scientists and business units.
• Build LLM applications, including RAG and Multi-Agent systems, and collaborate on AIOps challenges.
• Manage and improve the CI/CD ecosystem, automating release processes and resolving code issues.
• Standardize machine learning development practices and lead paired programming sessions to upskill the team.
• Implement infrastructure as code and manage containerized services in a cloud environment.

Required Skills

• 3+ years of backend software engineering experience in Python.
• 2+ years of experience with Cloud Engineering, specifically Google Cloud Platform (GCP).
• Hands-on experience with MLOps and Gen AI, including LLMs, RAG, and Multi-Agent applications.
• Proficiency with ML workflow orchestration tools such as Airflow or Kubeflow.
• Experience with DevOps tools including Jenkins, Tekton, Terraform, Bash, and PowerShell.
• Strong knowledge of Kubernetes and Docker for container management.
• Experience with GCP services like Vertex AI, Cloud Functions, and BigQuery.
• Bachelor’s degree in Computer Science, Computer Engineering, or a related technical discipline.

Preferred Skills

• Master’s degree in Computer Science, Machine Learning, or a related field.
• Advanced working knowledge of C/C++ alongside Python.

Key Skills

Education

Any Graduate