Principal Engineer, Machine Learning

👋🏼We're Nagarro.

We are a Digital Product Engineering company that is scaling in a big way! We build products, services, and experiences that inspire, excite, and delight. We work at scale across all devices and digital mediums, and our people exist everywhere in the world (17500+ experts across 39 countries, to be exact). Our work culture is dynamic and non-hierarchical. We're looking for great new colleagues. That's where you come in!

REQUIREMENTS:

• Should have experience to design end-to-end AI solution architectures for telecom-specific use cases (e.g., network optimization, predictive maintenance, customer churn prediction).
• Should be able to define scalable and modular architecture patterns for AI/ML pipelines, data ingestion, model training, and deployment.
• Must be able to ensure alignment with enterprise architecture standards and telecom regulatory requirements.
• Should be able to collaborate with data engineering teams to define data models, pipelines, and governance frameworks. 
• Integrate AI models with telecom systems such as OSS/BSS, CRM, and network management platforms.
• Should be able to define strategies for real-time and batch AI processing using telecom data (e.g., CDRs, network logs, customer interactions)
• Work closely with business analysts, product managers, and domain experts to translate telecom business needs into AI solutions.
• Should be able to present architectural decisions and trade-offs to senior leadership and clients.
• Should be able to guide cross-functional teams through technical feasibility assessments and solution roadmaps.
• Should be able to evaluate and select appropriate AI/ML frameworks, tools, and platforms (e.g., TensorFlow, PyTorch, Azure ML, AWS SageMaker).
• Must oversee model lifecycle management including training, validation, deployment, monitoring, and retraining.  Ensure responsible AI practices including fairness, explainability, and compliance.
• Should be able to define and enforce best practices for code quality, security, and performance in AI systems.
• Should be able to conduct architecture reviews, risk assessments, and performance tuning.
• Must ensure compliance with telecom-specific data privacy and security regulations (e.g., GDPR, TRAI). 
• Should be able to mentor junior architects and engineers in AI and telecom solution design.
• Should be able to stay updated on emerging AI trends in telecom (e.g., 5G, network slicing, autonomous networks).
• Should be able to drive innovation through PoCs and pilot projects with cutting-edge AI technologies.

RESPONSIBILITIES:

• Writing and reviewing great quality code
• Understanding the client’s business use cases and technical requirements and be able to convert them into technical design which elegantly meets the requirements.
• Mapping decisions with requirements and be able to translate the same to developers.
• Identifying different solutions and being able to narrow down the best option that meets the clients’ requirements.
• Defining guidelines and benchmarks for NFR considerations during project implementation.
• Writing and reviewing design document explaining overall architecture, framework, and high-level design of the application for the developers.
• Reviewing architecture and design on various aspects like extensibility, scalability, security, design patterns, user experience, NFRs, etc., and ensure that all relevant best practices are followed.
• Developing and designing the overall solution for defined functional and non-functional requirements; and defining technologies, patterns, and frameworks to materialize it.
• Understanding and relating technology integration scenarios and applying these learnings in projects.
• Resolving issues that are raised during code/review, through exhaustive systematic analysis of the root cause, and being able to justify the decision taken.
• Carrying out POCs to make sure that suggested design/technologies meet the requirements.

Bachelor’s or master’s degree in computer science, Information Technology, or a related field.