ML Operations Lead

Akaasa Infotech Noida; Pune District; On-site; INR 3,500,000 - 7,000,000; Full time

Job summary

Akaasa Infotech Noida in Pune seeks an experienced ML Operations Lead (Senior Manager) to manage and operate traditional ML models in production. You will lead a team, ensure model performance, monitor drift, and oversee retraining, deployment, and validation standards.

The role demands hands-on MLOps expertise, deployment pipelines, drift detection, backtesting, and collaboration with Data Engineering and cross-border Business teams. Immediate joiners preferred.

Qualifications

• Experience with MLOps and traditional ML models in production.
• Deployment, monitoring, drift detection, and retraining responsibilities.
• CI/CD pipelines, model registries, and lineage management.
• Champion-challenger testing, backtesting and validation practices.
• Familiarity with metrics like AUC and precision-recall.
• Experience with churn prediction or other predictive ML use cases.
• Strong team leadership and stakeholder communication.

Responsibilities

• Lead and mentor the ML Operations team.
• Manage ML model deployment, CI/CD pipelines, retraining, and rollback.
• Implement model monitoring and drift detection across systems.
• Handle model validation, backtesting, and champion-challenger testing.
• Maintain model registries, versioning, lineage, and performance metrics.
• Collaborate with Data Engineering, Business teams, and cross-border stakeholders.

Skills

MLOps

Model deployment

Model monitoring

Drift detection

CI/CD

Model registry & lineage

Backtesting & validation

Team leadership & communication

AUC & precision-recall metrics

Churn prediction & predictive ML use-c

Job description

Job Title: ML Operations Lead (Senior Manager)

Location: Pune

Work Mode: 5 Days Work from Office

Experience: 12+ Years

Notice Period: Immediate Joiners / Serving Notice

Job Description:

We are looking for an experienced ML Operations Lead to manage and operate traditional Machine Learning models in production. The role involves leading a team, ensuring model performance, monitoring drift, managing retraining, and maintaining deployment and validation standards.

Key Responsibilities:

• Lead and mentor the ML Operations team.
• Manage ML model deployment, CI/CD pipelines, retraining, and rollback.
• Implement model monitoring and data, feature, and concept drift detection.
• Handle model validation, backtesting, and champion-challenger testing.
• Maintain model registries, versioning, lineage, and performance metrics.
• Collaborate with Data Engineering, Business teams, and cross-border stakeholders.

Mandatory Skills:

• Strong hands-on experience in MLOps and traditional ML models in production.
• Model deployment, monitoring, drift detection, and retraining.
• CI/CD, model registries, and model lineage.
• Champion-challenger testing, backtesting, and model validation.
• Knowledge of model metrics such as AUC and precision-recall.
• Customer churn prediction and other predictive ML use cases.
• Team leadership, stakeholder management, and excellent communication.