ML Operations Lead - CI/CD Pipeline in Pune, भारत

Job Description : ML Operations Engineer - LeadDepartment : AI & Agent Operations (Day 2), AI OrganisationLocation : Pune, IndiaReporting To : Assistant Director, AI & Agent Operations (Singapore)Team Size : 2 ML Operations EngineersWork Schedule : Rotational ShiftsDomain : Information Technology (IT)Job Summary : We are looking for an experienced ML Operations Lead to manage the deployment, monitoring, maintenance, and optimization of traditional machine-learning models in production. The role will oversee predictive models across consumer, enterprise (B2B), and network businesses, including customer churn prediction, fraud detection, revenue assurance, and network capacity https://jobeax.com/link/cNGw9NQxVmlnL9El successful candidate will lead a team of two engineers in India, ensuring model accuracy, reliability, governance, and operational efficiency while coordinating with the Singapore leadership team. This role focuses on classical MLOps and traditional machine-learning models, not LLMs or Generative https://jobeax.com/link/1zoyWH1AVQN1pQPx Responsibilities : - Lead, mentor, and develop the India ML Operations team, establishing operational standards, priorities, and delivery timelines.- Manage production deployment, retraining, validation, and rollback of traditional ML models using CI/CD pipelines and structured validation processes.- Implement model monitoring to detect data, feature, and concept drift, model decay, and performance degradation; define appropriate retraining triggers and thresholds.- Establish and maintain model registries and lineage records, including model versions, training datasets, performance baselines, and last-known-good versions.- Ensure model changes requested by business stakeholders are implemented within agreed timelines and validated before deployment.- Apply champion-challenger testing, backtesting, and validation gates to ensure model reliability before promoting models to production.- Monitor model performance using appropriate metrics, including AUC, precision-recall, and other relevant evaluation measures.- Oversee bias and fairness monitoring for decision-making models, ensuring appropriate transparency and human oversight where required.- Collaborate with Data Engineering teams on data quality, data freshness, data contracts, and change notifications.- Coordinate with the Singapore leadership team on deployment schedules, incident management, shared services, and operational standards.- Report model health, deployment success, operational risks, and portfolio performance against defined KPIs.- Ensure adherence to data governance, model auditability, and applicable model-risk management https://jobeax.com/link/w1d7bRHtPmfLc8oX Qualifications & Experience : - Bachelor's degree in Computer Science, Data Science, Engineering, Statistics, or a related discipline.- 8+ years of experience in ML engineering, MLOps, or data science engineering, including team leadership.- Hands-on experience deploying, monitoring, and maintaining traditional machine-learning models in production.- Strong experience with model drift detection, retraining pipelines, model validation, and production deployment.- Proven experience with model CI/CD, model registries, lineage management, and rollback procedures.- Experience with champion-challenger frameworks, backtesting, and model performance evaluation.- Strong understanding of model governance, data quality, and bias/fairness monitoring.- Experience leading engineering teams and communicating effectively with business and technical https://jobeax.com/link/FfNN38MjANEx2m9w Qualifications : - Experience working with telecommunications-scale data and production ML environments.- Prior experience managing customer churn prediction models.- Familiarity with predictive use cases such as fraud detection, revenue assurance, and network capacity forecasting.- Experience with cloud-based machine-learning platforms.- Postgraduate qualification in ML/AI, Data Science, or another quantitative discipline.- Experience coordinating with international teams across geographies and time https://jobeax.com/link/EMIDuyBJYh3UayBD Competencies : - People leadership, mentoring, and team development.- Strong analytical and problem-solving skills.- Sound operational judgment and incident management.- Effective stakeholder communication and business requirement translation.- Ability to prioritize competing demands and manage production risks.- Strong coordination skills in a cross-border reporting environment.Decision-Making Responsibilities : 1. Independent authority : - Manage India team priorities and operational standards.- Initiate retraining, model promotion, and rollback decisions within approved validation procedures.- Take appropriate drift-response actions and escalate data-quality issues to Data Engineering.2. Escalation to leadership : - Enterprise risk acceptance and regulatory considerations.- Cross-functional priorities and standards affecting the wider AI and data ecosystem.- Headcount, budget, procurement, and changes impacting other platform or data https://jobeax.com/link/ktynEAIYM5uC9g10 Challenges : - Maintaining model accuracy and reliability across a diverse production portfolio.- Managing drift, model decay, and data-quality dependencies with a lean engineering team.- Coordinating deployments, incidents, and standards across India and Singapore.- Balancing predictive performance with fairness, transparency, and responsible model use. (ref:hirist.tech)