Job Description – Python Developer / ML Engineer – Banking & AI
Experience: 4–6 Years
Location: Pune / Mumbai
Employment Type: Full-Time
About the Role
We are looking for a Python Developer / ML Engineer with 4–6 years of experience to build and deploy scalable, production-grade AI/ML and transaction processing systems for the Banking & FinTech domain.
The ideal candidate should have strong expertise in Python and FastAPI, hands-on experience building REST APIs and microservices, and a solid understanding of ML model development and deployment.
This role requires someone who can design scalable systems, make sound technical decisions, and take ownership of solutions end-to-end, rather than simply implementing predefined development tickets.
Key Responsibilities
- Design, develop, and maintain high-performance Python applications and microservices using FastAPI.
- Build production-grade REST APIs and microservices with a focus on scalability, reliability, security, and maintainability.
- Develop, train, evaluate, and deploy Machine Learning models for real-world business use cases.
- Design systems capable of handling real-time transaction processing and event-driven workflows.
- Work with Apache Kafka, Redis, and Celery for asynchronous processing, event streaming, caching, and distributed task execution.
- Design and optimize database solutions using PostgreSQL, including complex queries, indexing, transactions, and performance optimization.
- Containerize applications using Docker and deploy/manage workloads on cloud platforms.
- Integrate applications with banking systems, payment platforms, third-party APIs, and FinTech services.
- Develop secure and resilient solutions suitable for financial transactions and sensitive customer data.
- Collaborate with product, business, data science, and engineering teams to translate business requirements into scalable technical solutions.
- Participate in system architecture and design discussions, including API design, data flow, scalability, fault tolerance, and integration patterns.
- Monitor, troubleshoot, and optimize applications running in production.
- Follow best practices around clean code, testing, CI/CD, observability, security, and version control.
Required Technical SkillsPython & Backend
- Strong hands-on experience with Python.
- Strong experience with FastAPI and API development.
- Proven experience building RESTful APIs and production-grade microservices.
- Good understanding of asynchronous programming, concurrency, and distributed systems.
Machine Learning
- Hands-on experience in ML model development, evaluation, and deployment.
- Understanding of the complete ML lifecycle, from data preparation and model development to production deployment and monitoring.
- Experience integrating ML models into backend/API-based applications.
- Familiarity with commonly used ML libraries such as scikit-learn, Pandas, NumPy, etc.
Real-Time & Distributed Systems
- Experience with Kafka for event streaming and real-time data processing.
- Experience with Redis for caching, queues, or high-performance data access.
- Experience with Celery or similar distributed task-processing frameworks.
- Understanding of event-driven and asynchronous architectures.
Database
- Strong experience with PostgreSQL.
- Good understanding of database design, query optimization, indexing, transactions, and data modelling.
DevOps & Cloud
- Hands-on experience with Docker.
- Exposure to cloud platforms such as AWS, Azure, or GCP.
- Understanding of CI/CD, application deployment, logging, monitoring, and production troubleshooting.
Banking / FinTech Experience
Experience working with Banking, FinTech, Payments, Financial Services, or Transaction Processing systems is highly preferred.
Exposure to any of the following will be a strong advantage:
- AML (Anti-Money Laundering)
- Fraud Detection
- KYC / Customer Verification
- Risk Scoring
- Transaction monitoring
- Credit/risk analytics
- Payment processing
- Financial transaction integrations
- Regulatory/compliance technology
System Design & Engineering Expectations
The candidate should be able to:
- Understand business requirements and convert them into technical architecture and system designs.
- Design APIs, microservices, data flows, and event-driven architectures independently.
- Identify scalability, performance, security, and reliability considerations before implementation.
- Make appropriate technology and architecture decisions based on business requirements.
- Build solutions that are maintainable, fault-tolerant, scalable, and production-ready.
- Take ownership of a feature or system from design → development → deployment → production support.
Qualifications
- Bachelor's or Master's degree in Computer Science, Information Technology, Engineering, Data Science, or a related field.
- 4–6 years of relevant professional experience in Python/backend development and/or ML engineering.
- Strong problem-solving and analytical skills.
- Good communication and collaboration skills.
- Ability to work independently and take ownership of technical deliverables.
Good to Have
- Experience with Kubernetes.
- Experience with AWS services such as EC2, ECS/EKS, Lambda, S3, RDS, etc.
- Experience with CI/CD tools and observability platforms.
- Knowledge of ML model serving frameworks and MLOps practices.
- Experience with authentication/authorization mechanisms such as OAuth2/JWT.
- Understanding of financial data security, compliance, and regulatory requirements.
Ideal Candidate Profile
We are looking for a hands-on engineer who combines strong Python/FastAPI backend expertise with practical ML experience and an understanding of real-time financial systems. The ideal candidate is capable of designing and owning scalable solutions end-to-end and is comfortable working across backend engineering, ML deployment, distributed systems, and Banking/FinTech integrations.
Work Location: In person
