About this role
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.