MLOps Manager

About LenDenClub:

LenDenClub is India’s largest RBI-registered (NBFC-P2P) Peer-to-Peer (P2P) lending platform. We are a platform for lenders seeking high interest with creditworthy borrowers, bridging the gap left by traditional credit institutions. With over 3 crore users and ₹16,000 crore+ in loans disbursed, we command more than 98% of India’s P2P lending market. Our 4.4+ rating on the App Store reflects our commitment to offering a trustworthy and secure lending experience. Powered by cutting-edge technology and a user-first approach, we are setting new benchmarks in India’s evolving fintech ecosystem. The progressive approach towards employee benefits has been acknowledged and appreciated and as a result, LenDenClub has been certified as a 'Great Place to Work' successively for four years by the Great Place to Work Institute, Inc.

About InstaMoney:

InstaMoney is our cutting-edge Loan Service Provider (LSP) platform, built to make borrowing fast, flexible, and fully digital for users across India. With over 30 million downloads, InstaMoney offers seamless credit access through a simple and intuitive mobile app. From Personal Loans and Merchant Loans, InstaMoney provides short- to mid-tenure credit solutions

Role Overview

We are looking for a Senior AI/ML & MLOps Engineer with 3–6 years of experience to build, deploy, and scale AI/ML systems in production. The role will combine AI/ML engineering, MLOps, backend/API development, cloud infrastructure, and AI platform optimization .

The person will work closely with AI, Product, Credit, Engineering, DevOps and Data teams to take AI initiatives from experimentation to reliable production systems.

Key Responsibilities

• •Design, develop, and deploy ML/AI models and AI-powered applications for production use cases.
• •Build and maintain MLOps pipelines for model training, evaluation, deployment, monitoring, and retraining.
• •Develop scalable APIs and backend services to integrate AI/ML models with business applications.
• •Own end-to-end productionization of AI solutions, including architecture, deployment, monitoring, and reliability .
• •Work on AWS/cloud infrastructure for AI and data workloads and optimize infrastructure for performance and cost.
• •Build frameworks and processes to monitor and control AI/LLM/API costs .
• •Implement model and system monitoring, including performance, drift, latency, failures, data quality, and business KPIs .
• •Work with data engineers to build reliable data pipelines and data platforms required for AI/ML systems.
• •Evaluate and integrate LLMs, GenAI models, AI agents, and third-party AI services where applicable.
• •Build experimentation frameworks to quickly evaluate new AI models, tools, and approaches.
• •Ensure AI systems are scalable, secure, observable and production-ready .
• •Troubleshoot production issues and work with DevOps/Engineering teams for quick resolution.
• •Maintain technical documentation, architecture decisions, deployment processes, and operational runbooks.
• •Drive engineering best practices around Git, CI/CD, Docker, cloud deployment, testing, and code quality .
• •Mentor junior engineers and contribute to technical design and architecture discussions.

Required Skills

• •3–5 years of experience in AI/ML Engineering, MLOps .
• •Strong Python programming skills.
• •Hands-on experience with ML model development and deployment .
• •Strong understanding of MLOps and ML lifecycle management .
• •Experience building and deploying REST APIs / microservices .
• •Experience with AWS or other cloud platforms .
• •Strong knowledge of Docker, Git, CI/CD, databases, and production deployment.
• •Experience with ML frameworks such as Scikit-learn, XGBoost, PyTorch, or TensorFlow .
• •Experience with model monitoring, data pipelines, logging, alerting, and observability.
• •Working knowledge of LLMs, GenAI, prompt engineering, RAG, or AI agents is preferred.
• •Good understanding of system design, scalability, performance and cost optimization.

Good to Have

• •Experience in FinTech, lending, credit, risk, or financial services .
• •Experience with Vertex AI, AWS ML services or equivalent ML platforms .
• •Experience building AI/ML platforms or reusable frameworks.
• •Experience with PostgreSQL and data engineering.
• •Experience optimizing cloud and AI infrastructure costs.
• •Experience working with autonomous/agentic AI systems.

What We Expect

• •Strong ownership from problem definition to production deployment .
• •Ability to work independently and handle ambiguous AI/ML problems.
• •Strong collaboration with Product, Engineering, DevOps, Data, and Business teams.
• •Focus on building reliable, scalable, and cost-efficient AI systems , not just models or prototypes.