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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