Sr Manager

3 weeks ago


Delhi, Delhi, India Tata Communications Limited Full time
Job Description

Job Description

Responsible for architecting and deploying solutions that combine machine learning models with full stack applications using Java and Python. This role focuses on integrating data pipelines, model inference, and API-driven front-end interfaces to automate workflows and optimize performance across systems. Drives implementation strategies aligned to product requirements and engineering standards.

Responsibilities

Understand IoT-specific requirements including data ingestion from edge devices, analytics needs, and user-facing application features.

Lead technical discussions with cross-functional teams (e.g., hardware, cloud, analytics) to evaluate feasibility, define specifications, and assess performance and scalability for IoT solutions.

Define and design software architecture for integrating IoT data pipelines, ML models, and full stack applications using Java and Python.

Deliver robust features including sensor data processing, real-time analytics dashboards, and APIs for device management and control.

Drive deployment of end-to-end IoT platforms from data collection and ML model deployment to web/mobile access with a focus on automation and resilience.

Review and finalize infrastructure design including edge-cloud integration, containerized services, and streaming data solutions (e.g., Kafka, MQTT).

Create and manage user stories for device-side logic, cloud-based processing, and visualizations, ensuring seamless interaction across systems like OSS-BSS and enterprise applications.

Establish standards for edge computing, MLOps in IoT, and cloud-native application development (SaaS/IoT PaaS), ensuring security, scalability, and maintainability.

Facilitate prioritization of features related to device data processing, predictive maintenance, anomaly detection, and real-time user interfaces.

Desired Skill Sets

Strong experience architecting and deliveringSoftware applicationscombiningreal-time data,machine learning, andcloud-native full stack platforms.

Hands-on expertise withJava (Spring Boot)andPythonfor both backend services and ML model implementation.

Experience with IoT protocols (MQTT, CoAP), data streaming (Kafka, AWS Kinesis), and edge-cloud data integration.

Deep understanding of software/application lifecycle management for connected device platforms.

Experience working in Agile setups and DevOps pipelines with tools like Docker, Kubernetes, Jenkins, Git

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