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Qodequay Technologies Pvt ltd

Python Developer / ML Engineer – Banking & AI

  • غير محدد

نُشرت قبل 22 ساعة

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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

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