BD/ Inside Sales role.

Jobitus; Navi Mumbai; On-site; INR 400,000 - 640,000; Full time

Job summary

Jobitus is seeking a Senior Platform Engineer – MLOps in Navi Mumbai to design, build, and maintain scalable ML infrastructure and workflows. You will work with data scientists, ML engineers, and DevOps to implement MLOps solutions and ensure smooth production deployment.

You will mentor junior engineers, promote best practices, and stay current with MLOps trends and tooling to continuously improve the platform.

Qualifications

• 5+ years in platform engineering with a focus on MLOps.
• Experience building and maintaining ML CI/CD pipelines.
• Hands-on with Kubeflow, MLflow, and Airflow.
• Proficiency in AWS, GCP, or Azure cloud platforms.
• Strong Docker and Kubernetes knowledge.
• Python scripting and automation skills.
• Understanding of model lifecycle: training, deployment, monitoring.

Responsibilities

• Design end-to-end MLOps pipelines for CI/CD and model versioning.
• Architect scalable cloud infrastructure with Kubernetes & Docker.
• Deploy, monitor, and maintain production ML models.
• Automate ML workflows from data ingestion to monitoring.
• Collaborate with data scientists and DevOps teams.
• Mentor junior engineers and promote DevOps practices.
• Stay updated with the latest MLOps trends and tools.

Skills

MLOps

CI/CD pipelines

Cloud platforms

Kubernetes

Docker

Python

Model lifecycle

Monitoring

Team mentoring

Collaboration

Tools

Kubeflow

MLflow

Airflow

Prometheus

Grafana

Job description

Role Overview

As a Senior Platform Engineer – MLOps, you will play a key role in designing, building, and maintaining the infrastructure and workflows that support our machine learning systems. You’ll work closely with data scientists, ML engineers, and DevOps teams to implement scalable MLOps solutions, mentor team members, and ensure smooth deployment and operation of ML models in production environments.

Key Responsibilities

• Design and implement end-to-end MLOps pipelines for CI/CD, model versioning,
• Architect and manage scalable infrastructure using cloud platforms (AWS/GCP/Azure) with Kubernetes and Docker.
• Deploy, monitor, and maintain production-grade ML models, ensuring performance, reliability, and compliance.
• Automate ML workflows, including data ingestion, model training, testing, deployment, and monitoring.
• Collaborate with cross-functional teams to integrate ML solutions into broader platform ecosystems.
• Mentor junior DevOps and MLOps engineers, promoting best practices and a strong DevOps culture.
• Stay up to date with the latest trends and tools in MLOps to continuously improve the platform.

Required Skills & Experience

• 5+ years of experience in platform engineering with a strong focus on MLOps.
• Hands-on expertise in building and maintaining CI/CD pipelines for ML models.
• Experience with MLOps tools such as Kubeflow, MLflow, Airflow, etc.
• Proficiency in cloud platforms: AWS, GCP, or Azure.
• Strong knowledge of containerization and orchestration: Docker and Kubernetes.
• Programming experience in Python (Go is a plus) for scripting and automation.
• Solid understanding of model lifecycle management: training, validation, deployment, and monitoring.
• Familiarity with monitoring and logging tools (e.g., Prometheus, Grafana).
• Excellent problem-solving and collaboration skills, with experience in team leadership or mentoring.