Top Machine Learning Jobs in Bangalore

Provide Tier 2/3 diagnostics and remediation for 4G/5G core outages, drive root-cause analysis, mentor NOC staff, implement AI-driven diagnostics, and reduce MTTR to maintain network uptime.

Lead Tier 2/3 diagnostics and resolution for 4G/5G core outages in cloud-native environments. Drive RCA, reduce MTTR, implement AI diagnostics, mentor NOC, and liaise with Tier 1/2 providers to maintain network stability.

Lead diagnostics and resolution of complex Tier 2/3 4G and 5G core incidents in cloud-native environments. Drive root-cause and chronic-incident analysis, reduce MTTR, implement AI-driven monitoring, and provide technical guidance and training to the NOC. Collaborate with Tier 1/2 providers and validate network functions running in Kubernetes and cloud infrastructure.

Lead Tier 2/3 troubleshooting and RCA for 4G/5G core (IMS/packet core) in cloud-native Kubernetes environments. Drive MTTR reduction, implement AI diagnostics, mentor the NOC team, and perform chronic incident analysis to improve network uptime and stability.

Lead architecture and technical strategy for a global Reviews platform: design resilient, low-latency, cloud-native services; contribute hands-on code; collaborate with product and data science for ML-powered insights; ensure high availability, observability, compliance; mentor engineers and drive cross-domain platform modernization.

Design and build reliable, performant, and secure platform building blocks for a conversational AI platform. Own platform roadmap, build scalable microservices and enterprise data platforms, partner across teams, deliver interdependent projects, and participate in code and design reviews to improve the platform continuously.

Senior-level Java software engineer contributing to design, development, testing, and operational stability of distributed microservice applications. Drive engineering standards, lead POCs and AI innovation, adopt CI/CD and automation, mentor teams, and ensure secure, resilient, high-quality delivery across cloud and enterprise environments.

Lead engineering teams to design and deliver cloud-native, large-scale full-stack and microservices solutions on AWS/Azure/GCP; collaborate with product and analytics to build intelligent data products; mentor engineers, evaluate code, and drive technical strategy using Kubernetes and serverless infrastructure.

Lead architecture for software products across cloud-native domains (AWS), drive technical governance, evaluate and adopt emerging technologies (AI/ML/LLM), produce and review secure production code, guide integration and service design, mentor teams, and influence product and operational decisions.

The Engineering Lead will design and implement technical features, work on ML pipelines, and mentor engineers while ensuring high-quality deliverables. This role requires collaborating with teams and managing the ML lifecycle for business value.

Designs, develops, tests, and maintains secure, scalable software across the SDLC. Produces architecture artifacts, debugs complex systems, leverages AI-assisted development tools, analyzes large data sets to improve code and architecture, and contributes to engineering communities while promoting secure and resilient application practices.

Design and implement technical features, collaborate with clients, write production-ready code, ensure quality deliverables, mentor team members, and implement ML models on large scale.

Design and deliver end-to-end packet core and 5G core solutions, optimize network performance, collaborate with product, R&D and customer teams, lead transformations, perform protocol and data analysis, and support deployment and knowledge transfer.

Design and implement scalable backend services, lead full software lifecycle, write design docs, mentor engineers, collaborate cross-functionally, improve performance and quality, and integrate AI tools to boost development productivity.

Build data-driven solutions and BI using Python, Power BI, and SQL. Implement DevOps pipelines with GitHub Actions/Azure DevOps, deploy on Azure/AWS, integrate APIs, apply unit testing and automation, and collaborate in Agile/Scrum with global teams. Support solution design, effort estimates, and use ML/DL/LLMs for intelligent features.

Manage and grow a team responsible for observability, monitoring, and integrations across monetization systems. Improve reliability and data quality for billing, provisioning, subscriptions, and revenue-impacting workflows; define telemetry and integration strategies; implement anomaly detection and incident management; and partner with cross-functional stakeholders to ensure reliable customer and financial workflows.

Lead technical direction and delivery for a core NIRA backend domain: design and ship high-volume web APIs, own architecture for distributed and queue-based systems, drive complex initiatives, mentor engineers, lead incident response, champion AI dev tools, and align cross-functionally to simplify systems and influence roadmap.

Define technical vision and architecture for large-scale distributed, cloud-based systems. Contribute hands-on to core code, optimize data pipelines, ensure reliability and low-latency performance, mentor engineers, collaborate with product and Ads/Bing teams, resolve production issues, and apply AI tools to improve engineering workflows.

The Engineering Manager for Sales Systems will lead a team to develop scalable sales systems and improve engineering standards and processes while collaborating with various stakeholders.

Design and implement robust backend services, APIs, and integrations for an Agentic AI platform. Write and maintain backend code (Python/C#/.NET), implement APIs, databases, containerized deployments, unit tests, and collaborate with frontend and stakeholders to ensure scalable, maintainable enterprise-grade systems.

Design, implement, and maintain scalable backend services and APIs for an Agentic AI platform. Develop server-side logic in Python and C#/.NET, integrate databases and LLM/ML systems, deploy with Docker/Kubernetes on Azure, write unit tests, perform code reviews, and collaborate with front-end and stakeholders to ensure reliable enterprise integrations.

Lead architecture and deliver custom .NET full‑stack solutions, design scalable microservices and APIs, drive cloud/DevOps and AI modernization, mentor engineers, and steer architectural governance and platform convergence to meet product and organizational goals.

Lead design and delivery of custom, scalable SaaS solutions using .NET full-stack. Provide technical leadership, architecture, CI/CD and cloud expertise, mentor engineers, collaborate with stakeholders, and drive AI/DevOps modernization.

Lead design and delivery of custom, scalable SaaS solutions using .NET full-stack and cloud platforms. Provide technical leadership, architecture, CI/CD and DevOps, mentor engineers, collaborate with stakeholders, and drive AI/LLM and automation initiatives.

Lead architecture and engineering efforts to design, build, and improve scalable .NET full-stack systems. Drive technical design, governance, microservices and API strategies, mentor teams, guide cloud/DevOps modernization, and translate AI/LLM innovations into business value while ensuring reliability, security, and performance across applications.