Principal Engineer - AI Science

What youll be doing...

The role requires expertise in developing next-generation AI/ML models to improve network planning, engineering, and assurance platforms thereby improving the customer experience.

Network AI as a core competency, and you will lead the AI use cases to improve network visibility, proactive maintenance and monitor performance degradations across the global network footprint.

Help internal network monitoring teams perform smooth day-to-day operations by building AI models to improve efficiency in troubleshooting and reduce MTTR/tickets.

You will be responsible for:

• Driving AI-infused network use cases with cross-functional teams delivering business value.
• Identifying and defining new process improvement and or business opportunities.
• Contributing to the GenAI solutions to reduce the network engineers cognitive load.
• Data mining or extracting usable data from valuable data sources.
• Mentoring and Moulding team with guidance and support in modelling and delivery.
• Working closely with management to prioritize business and information needs.
• Gathering / Focusing on functional and non-functional requirements from business stakeholders.
• Following all the ML lifecycle procedures defined by the responsible AI framework.
• Articulating the story behind the solution in every stage through executive presentations.
• Managing internal/external stakeholders and executive leadership.
• Building a culture of innovation with cross-functional teams.
• Participating in internal and external forums.

What were looking for...

Youll need to have:

• Bachelors degree or four or more years of work experience.
• Six or more years of relevant work experience.
• Experience with modelling techniques, applications, and implementations using Statistics (Hypothesis testing, Discriminant analysis, Linear/Logistic regression, PCA, vector analysis), Forecasting (Time Series), Machine Learning (Classification, Clustering, Collaborating filtering) and AI Algorithms (GenAI/NLP, Deep Learning, Cognitive Analytics, Optimization, Non-Linear Algorithms).
• Experience working with GCP, Big Query/SQL, Python and Spark
• Experience in writing complex queries to extract the data to build and derive the model features to draw business insights.

Even better if you have one or more of the following:

• Two or more years of experience in the telecom network domain.
• Two or more years of experience with developing and deploying machine learning models to production.
• Experience in building scoring models, and anomaly detection solutions.

In this hybrid role, you'll have a defined work location that includes work from home and assigned office days set by your manager.

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