Job Description - Full Stack Developer_AI/ML Engineer

Position: Full Stack Developer + AI ML Engineer

Location: Bangalore, India (Hybrid)

Employment Type: [Full-Time]

Why should you choose us

Rakuten Symphony is reimagining telecom, changing supply chain norms and disrupting outmoded thinking that threatens the industry's pursuit of rapid innovation and growth. Based on proven modern infrastructure practices, its open interface platforms make it possible to launch and operate advanced mobile services in a fraction of the time and cost of conventional approaches, with no compromise to network quality or security.

Rakuten Symphony has operations in Japan, the United States, Singapore, India, South Korea, Europe, and the Middle East Africa region. For more information, visit: https://symphony.rakuten.com.

Building on the technology Rakuten used to launch Japan's newest mobile network, we are taking our mobile offering global.

To support our ambitions to provide an innovative cloud-native telco platform for our customers, Rakuten Symphony is looking to recruit and develop top talent from around the globe. We are looking for individuals to join our team across all functional areas of our business – from sales to engineering, support functions to product development.

Let's build the future of mobile telecommunications together!

About Rakuten Group, Inc. (TSE: 4755) is a global leader in internet services that empower individuals, communities, businesses and society. Founded in Tokyo in 1997 as an online marketplace, Rakuten has expanded to offer services in e-commerce, fintech, digital content and communications to 2 billion members around the world. The Rakuten Group has over 30,000 employees, and operations in 30 countries and regions. For more information visit https://global.rakuten.com/corp/.

What Do We Expect From You

We are seeking a skilled and motivated Full Stack Developer_AI/ML Engineer to join our team in India. The ideal candidate will be responsible for developing AI-driven applications, including intelligent telecom solutions, end to end. We are looking for a hands-on engineer with strong full-stack software development skills, hands-on Docker and Kubernetes experience to build images and support deployment workflows, and practical AI/ML and data science capability to build, integrate, test, and productionize models within the application. Working knowledge of MLOps practices for deployment, monitoring, and model lifecycle management is preferred, but this is not a pure MLOps role. Experience in telecom or related application environments is a plus.

Key Responsibilities:

1. Full Stack Development

Design, develop, and enhance production-grade applications using a full-stack engineering approach spanning backend services, APIs, data workflows, microservices, and user-facing components where required.
Build clean, maintainable, and scalable software with strong engineering discipline, code quality, version control, reusable design patterns, and production readiness.

2. Docker, Kubernetes & Deployment Engineering

Contribute to container-based and cloud-native solution design for scalable, secure, and resilient applications deployed across cloud or hybrid environments.
Build Docker images, work with Kubernetes-based deployment patterns, and support containerized application packaging, service integration, observability, and operational readiness for production systems.
Apply practical MLOps practices for model packaging, deployment, monitoring, and lifecycle support as part of end-to-end solution delivery.

3. AI/ML & Data Science Implementation

Apply AI/ML, analytics, and data science techniques to solve business and network problems, including prediction, optimization, anomaly detection, automation, and decision support use cases.
Work hands-on with data analysis, feature engineering, model development, model evaluation, and integration of trained models and intelligent logic into software components.

4. Testing, Deployment & Production Support

Own unit testing, integration testing, system validation, release readiness, and deployment activities to ensure robust production delivery.
Support field validation, troubleshooting, performance tuning, issue resolution, FOA activities, and production stabilization for delivered solutions.

5. Cross-Functional Delivery Ownership

Collaborate with product owners, platform teams, architects, QA teams, operations teams, and business stakeholders to drive end-to-end solution delivery.
Continuously improve engineering practices, container deployment standards, testing methods, and reusable frameworks for faster and more reliable delivery.

Skills and Qualifications

Education

Bachelor's or Master's degree in Computer Science, Data Science, Engineering, Electronics, Telecommunications, or a related field.

Technical Expertise

Strong software development skills with hands-on experience in full-stack engineering, including backend development, API design, system integration, data workflows, and frontend understanding where needed.
Strong understanding of distributed systems, microservices, containerization, and scalable application deployment principles.
Proficiency in Python, Linux, shell scripting, Git, and modern software engineering practices for building production-grade applications.
Hands-on experience in AI/ML and data science, including exploratory data analysis, feature engineering, model development, model evaluation, and integration of AI/ML models into applications.
Hands-on experience with Docker and Kubernetes, including container image creation, packaging, deployment workflows, CI/CD pipelines, automated testing, and operational support for cloud-native systems.
Working knowledge of MLOps concepts such as model deployment, monitoring, versioning, and lifecycle management is preferred.

Analytical & Problem-Solving Skills

Ability to understand business and technical problems, convert them into practical solution designs, and deliver scalable implementations with measurable impact.
Strong troubleshooting and critical thinking skills with attention to quality, performance, reliability, and end-to-end ownership.

Communication & Collaboration

Effective communicator with the ability to explain technical design, architecture choices, AI/ML logic, and deployment plans clearly to both technical and non-technical audiences.
Comfortable working in cross-functional teams and contributing across design, development, testing, deployment, and production support stages.

Preferred Qualifications

Experience in telecom, network analytics, automation platforms, or AI-driven operational use cases is a plus.
Experience with RIC concepts, related application environments, or similar production platforms is a plus.
Familiarity with cloud cost optimization, security, governance, and production monitoring practices is an advantage.
Exposure to FOA, production rollout governance, event-driven architectures, streaming pipelines, or platform integration patterns is beneficial.

Rakuten Shugi Principles:

Our worldwide practices describe specific behaviours that make Rakuten unique and united across the world. We expect Rakuten employees to model these 5 Shugi Principles of Success.

Always improve, always advance. Only be satisfied with complete success - Kaizen.
Be passionately professional. Take an uncompromising approach to your work and be determined to be the best.
Hypothesize - Practice - Validate - Shikumika. Use the Rakuten Cycle to success in unknown territory.
Maximize Customer Satisfaction. The greatest satisfaction for workers in a service industry is to see their customers smile.
Speed!! Speed!! Speed!! Always be conscious of time. Take charge, set clear goals, and engage your team.

Senior AI/ML Engineer

Senior Software Engineer + AI/ML Engineer