Top Machine Learning Jobs in Bangalore

Lead design, build, and maintain secure, scalable software systems; write and review production-quality Python code; drive adoption and safe use of enterprise AI-assisted engineering tools; improve automation, resiliency, and operational stability; evaluate vendors and lead engineering communities of practice within Commercial and Investment Banking.

Design, build, and maintain backend distributed systems and core infrastructure services (configuration, rate limiting, feature flags, A/B testing). Improve performance, scalability, and observability of cloud infrastructure. Deliver cross-team, deadline-sensitive features end-to-end and influence the infrastructure roadmap.

Build end-to-end internal audit applications and dashboards to automate control testing and continuous risk monitoring. Integrate data pipelines, LLMs/ML, and cloud-native microservices to deliver near real-time risk insights and partner with auditors and data engineers on telemetry and deployments.

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.

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.

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.

Perform end-to-end system verification of Ericsson 5G RAN solutions, including capacity, performance, scalability, mobility, and high-load traffic testing. Analyze logs, traces, KPIs, and protocol-layer behavior; troubleshoot PHY/MAC/RLC/PDCP/IP issues and identify root causes. Support feature integration, test automation, verification frameworks, and CI/CD improvements. Collaborate with development, integration, CI, and product teams while applying modern and AI-assisted verification methods.

Own customer service requests from contract validation through resolution, including emergency network restoration, SLA and KPI oversight, proactive fault prevention, data-driven support, and customer-network software implementations. Diagnose unsuccessful software loads, implement corrective actions, improve support processes, and build customer relationships through consultation, negotiation, knowledge sharing, and change management.

Principal Engineer responsible for enterprise-scale architecture and engineering strategy for high-scale consumer platforms. The role designs distributed Java and Python systems, AI/LLM-powered experiences, microservices, streaming architectures, and resilient cloud platforms. Responsibilities include technical leadership, platform engineering, CI/CD, quality engineering, performance optimization, observability, security, responsible AI, innovation, and collaboration with product, UX, data science, and executive stakeholders.

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.

Designs, audits, and optimizes telecom networks across RAN, Transport, Core, OM and Services. Supports pre-sales with technical analysis, proposes scopes and estimates costs, documents service offerings, and applies automation and ML analytics to drive network performance and efficiency while managing stakeholder and financial aspects.

Design, build, and lead enterprise-scale observability and telemetry solutions across on‑prem and cloud platforms. Develop full‑stack microservices, monitoring integrations (Prometheus/Grafana/OpenTelemetry), and AI-powered observability features for anomaly detection, root-cause analysis, and automation. Influence standards, mentor peers, and collaborate with stakeholders to deliver scalable, secure production systems.

Lead an agile team to design, develop, and deliver secure, resilient full-stack applications. Produce high-quality Java/React code, drive CI/CD and automation, adopt AI-assisted engineering practices, evaluate architectures, and improve operational stability and testing.

Design, build, and operate observability, anomaly detection, and reconciliation tooling for monetization systems. Implement metrics/logs/traces, automated billing and data anomaly detection, SLOs, runbooks, incident response, and collaborate with product, finance, and support. Leverage telemetry and machine learning to predict and resolve monetization issues, and guide technical direction for reliability and detection work.

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 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.

Lead a team building user-facing product features that leverage the ML platform. Design scalable, reliable frameworks and APIs, develop full-stack features, resolve production issues, ensure performance and security, and collaborate across teams while participating in code and design reviews.

Lead a Core Platform engineering team to design and build scalable, reliable backend and API product features that integrate with ML systems. Drive service-oriented architecture evolution, implement frameworks for rapid feature development and deployment, resolve production issues, participate in code/design reviews, and support continuous delivery in a high-concurrency environment.

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.

The posting contains only company overview and benefits; no specific responsibilities listed. A Principal Engineer typically leads technical architecture, owns complex systems, mentors engineers, drives technical strategy, and collaborates cross-functionally to ensure delivery and quality.

Leads the design, development, and maintenance of scalable search and backend systems. Deploys and manages machine learning models with data science teams, optimizes search algorithms and ML pipelines, integrates APIs and services, and contributes to architecture, code reviews, and engineering best practices. The role also includes technical leadership, mentoring, and collaboration across stakeholders.

Lead and grow a Physical Design Methodology & CAD team in India to define RTL-to-GDSII flows, automation, sign-off solutions, and AI-driven CAD transformations. Partner globally with architecture, design, verification, infrastructure, and EDA vendors to deliver scalable SoC/ASIC development, improve productivity, quality, and time-to-market.

Lead and scale engineering teams to build massively scalable software and systems; architect low-latency infrastructure; proactively guard against cyber threats; apply machine learning and financial engineering to turn data into action in a fast-paced global environment.

Provides technical vision and strategic leadership for a cloud-based network management platform. Defines long-term architecture and product roadmaps, leads innovation in AI-driven operations, intent-based networking, automation, and cloud-native networking, and guides platform evolution. Advises enterprise customers, develops vendor and cloud partnerships, supports acquisition due diligence, contributes to standards and open-source projects, represents the company publicly, and shapes engineering culture.