ML Operations Lead

Northridge Partner; Pune District; On-site; INR 1,800,000 - 2,400,000; Full time

Job summary

Northridge Partner in Pune, India, seeks an experienced ML Operations Lead to head the ML Operations team responsible for production deployment and ongoing management of traditional ML models.

You will drive model monitoring, validation, retraining, and governance, collaborating with data engineering, business stakeholders, and the Singapore leadership to ensure reliable, scalable ML outcomes across consumer and enterprise use cases.

Qualifications

• 17 to 25 years of overall professional experience in ML, MLOps or Data Science Engineering.
• Demonstrated experience managing and leading technical teams.
• Proven experience operating traditional ML models in production environments.
• Experience working with large-scale data environments.
• Ability to engage with business stakeholders and translate business requirements into technical deliverables.
• Bachelor's degree in Computer Science, Data Science, Engineering, Statistics or a related discipline.
• Postgraduate qualification in AI, ML or a quantitative discipline is an advantage.

Responsibilities

• Lead and mentor a team of ML Operations Engineers, establishing operational standards, priorities and best practices.
• Own the deployment, monitoring, retraining and validation of traditional ML models in production.
• Implement and manage model monitoring frameworks covering data drift, feature drift and concept drift.
• Establish model validation processes, including backtesting and champion-challenger methodologies, before production deployment.
• Manage model deployment, version control, rollback procedures and model performance optimisation.
• Maintain model lineage, registries, training data records and auditability.
• Monitor model performance, accuracy, fairness and reliability across business use cases.
• Work closely with Data Engineering teams to ensure data quality, freshness and consistency.
• Partner with business stakeholders to understand requirements and deliver model changes within agreed timelines.
• Coordinate with the Singapore-based AI & Agent Operations leadership team on operational standards, incidents and deployment schedules.
• Track and report model health, deployment success and operational KPIs.

Skills

MLOps

Traditional ML deployment

Churn prediction

Model monitoring

Retraining pipelines

Backtesting / champion-challenger

Model performance metrics

CI/CD pipelines

Cloud ML platforms

Governance / fairness

Education

Bachelor's degree in Computer Science / Data Science / Engineering / Statistics

Postgraduate AI/ML qualification (advantage)

Job description

Function: AI & Agent Operations

About the Role

We are hiring an experienced ML Operations Lead for a leading organisation's AI & Agent Operations function.

The role will lead the Machine Learning Operations team in Pune ,India, responsible for managing and optimising traditional Data Science and Machine Learning models deployed in production.

The successful candidate will oversee the operational lifecycle of predictive ML models across consumer, enterprise (B2B) and network businesses, ensuring model accuracy, reliability, scalability and performance.

This is a classical MLOps leadership role focused on traditional machine learning models, NOT LLM or Generative AI operations.

Key Responsibilities

• Lead and mentor a team of ML Operations Engineers, establishing operational standards, priorities and best practices.
• Own the deployment, monitoring, retraining and validation of traditional ML models in production.
• Implement and manage model monitoring frameworks covering data drift, feature drift and concept drift.
• Establish model validation processes, including backtesting and champion-challenger methodologies, before production deployment.
• Manage model deployment, version control, rollback procedures and model performance optimisation.
• Maintain model lineage, registries, training data records and auditability.
• Monitor model performance, accuracy, fairness and reliability across business use cases.
• Work closely with Data Engineering teams to ensure data quality, freshness and consistency.
• Partner with business stakeholders to understand requirements and deliver model changes within agreed timelines.
• Coordinate with the Singapore-based AI & Agent Operations leadership team on operational standards, incidents and deployment schedules.
• Track and report model health, deployment success and operational KPIs.

Required Technical Skills

• Strong expertise in MLOps and production machine learning operations.
• Hands‑on experience with traditional ML model deployment and lifecycle management.
• Experience in customer churn prediction models is highly desirable.
• Strong understanding of model monitoring and drift detection.
• Experience building and managing model retraining pipelines.
• Knowledge of model validation, backtesting and champion‑challenger frameworks.
• Understanding of model performance metrics, including AUC, precision, recall and model decay.
• Experience with ML CI/CD pipelines, model registries and lineage management.
• Exposure to cloud‑based ML platforms.
• Understanding of model governance, bias and fairness monitoring.

Experience & Qualifications

• 17 to 25 years of overall professional experience, with relevant experience in ML, MLOps or Data Science Engineering.
• Demonstrated experience managing and leading technical teams.
• Proven experience operating traditional ML models in production environments.
• Experience working with large-scale data environments.
• Ability to engage with business stakeholders and translate business requirements into technical deliverables.
• Bachelor's degree in Computer Science, Data Science, Engineering, Statistics or a related discipline.
• Postgraduate qualification in AI, ML or a quantitative discipline is an advantage.

Preferred Industry Experience

Experience in telecommunications or large-scale consumer data environments will be an advantage.

Exposure to predictive ML use cases such as:

• Customer churn prediction
• Fraud detection
• Revenue assurance
• Network capacity forecasting

Leadership Expectations

The role requires a strong technical leader who can balance hands‑on MLOps expertise with people management, operational discipline and stakeholder engagement.

The candidate should be comfortable working with cross‑functional and international teams, particularly across India and Singapore.

Important: This position focuses on traditional Machine Learning Operations and production ML models. It is not an LLM Ops or Generative AI‑focused position.