ML Ops

About Ascendion

Ascendion is a leader in AI-Native platform driven software engineering company that underwrites outcomes, helping businesses innovate faster, smarter, and with greater impact. We partner with Global 2000 clients across North America, UK, Europe, and APAC to solve complex challenges in data, experience design, software product engineering, and workforce transformation. Powered by expert engineers, thousands of AI agents, and our Engineering to the Power of AI™ (EngineeringAI) method, we deliver measurable outcomes that build trust, unlock value, and accelerate growth. Learn more at ascendion.com

Ascendion | Engineering to elevate life

We have a culture built on opportunity, inclusion, and a spirit of partnership. Come, change the world with us:

• Build the coolest tech for world's leading brands

• Solve complex problems – and learn new skills

• Experience the power of transforming digital engineering for Fortune 500 clients

• Master your craft with leading training programs and hands-on experience

Experience a community of change makers! Join a culture of high-performing innovators with endless ideas and a passion for tech. Our culture is the fabric of our company, and it is what makes us unique and diverse. The way we share ideas, learning, experiences, successes, and joy allows everyone to be their best at Ascendion.

About the Role

We are looking for a DevOps Engineer to join our team. In this role, you will build, deploy, and maintain machine learning models in development, staging, and production environments.

Job Title: ML Ops

Key Responsibilities:

• Build, deploy, and maintain machine learning models in development, staging, and production environments.

• Develop and manage ML pipelines for model training, validation, deployment, and monitoring.

• Implement CI/CD/CT pipelines for machine learning workflows.

• Manage model versioning, experiment tracking, and reproducibility.

• Monitor model performance, data drift, model drift, latency, and infrastructure health.

• Work with Data Scientists and ML Engineers to productionize ML models.

• Develop scalable and reliable ML infrastructure using cloud platforms.

• Implement model rollback, retraining, and alerting mechanisms.

• Ensure security, governance, and access control for ML systems.

Minimum Qualifications:

• Automate model deployment and infrastructure provisioning.

• Required Skills

• Programming

• Python — strong proficiency

• Bash/Shell scripting

• Familiarity with APIs and REST services

• ML & MLOps

• Understanding of machine-learning lifecycle

• Model training and deployment

• Model serving and inference

• Feature engineering pipelines

• Model/version management

• Experiment tracking

• Model monitoring and drift detection

• MLOps Tools

• MLflow

• Kubeflow

• Airflow

• DVC

• Weights & Biases

• DevOps

• Docker

• Kubernetes

• Git/GitHub/GitLab

• Jenkins / GitHub Actions / GitLab CI

• CI/CD pipelines

• Infrastructure as Code — Terraform preferred

Location: Pune

Want to change the world? Let us know. Tell us about your experiences, education, and ambitions. Bring your knowledge, unique viewpoint, and creativity to the table. Let's talk!