Top Machine Learning Jobs in Bangalore

Partners with enterprise customers to understand requirements, design AI solution architectures, and guide production deployments. Builds integrations, prototypes, reusable tools, and technical assets while troubleshooting complex issues. Leads technical workshops, collaborates with Product and Engineering teams, and shares customer feedback to improve the platform. The role combines software engineering, customer engagement, AI deployment, and scalable solution development.

Design and deploy scalable AI solutions for enterprise customers. Build integrations, prototypes, reusable tools, and production-grade applications; lead technical workshops; troubleshoot complex issues; document best practices; and collaborate with Product and Engineering teams to improve the platform based on customer feedback.

Develop API-first, cloud-native internal product creation tools for Nike’s Consumer Product & Innovation teams. Collaborate with engineers, product managers, principal engineers, and cross-functional technology teams. Build modular services and modern web application capabilities using frontend frameworks, AWS products, DevOps, infrastructure as code, CI/CD, microservices, REST, and domain-driven design. Apply modern testing practices and support software architecture and engineering initiatives.

Design and implement scalable software architectures for semiconductor equipment solutions. Develop prototypes, lead complex software components, conduct technical reviews, mentor engineers, evaluate technologies, mitigate technical risks, and contribute to high-level and low-level design. The role requires expertise in Java, Spring Boot, microservices, workflow frameworks, reactive programming, algorithms, and large-scale systems.

Lead and grow a backend engineering team building scalable, cloud-agnostic infrastructure and services for big data and ML workloads. Hire engineers, enforce technical standards, partner with product and customers, define roadmap, and coordinate cross-team execution to deliver reliable, monitored, and tested systems at scale.

Lead technical vision and architecture for large-scale, low-latency data systems; contribute hands-on to core code and production support; drive cross-team alignment; mentor engineers; refine data pipelines and CI/CD; apply AI tools to improve workflows; collaborate with Ads and Bing to integrate shared infrastructure and deliver reliable, scalable platforms.

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.

Develop and maintain automated quality testing for enterprise data products, pipelines, transformations, APIs, and platform capabilities. Validate data correctness, completeness, freshness, consistency, and lineage; build reconciliation and monitoring frameworks; design regression suites; and investigate production data-quality issues. The role also evaluates AI-powered analytics capabilities by validating user intents, creating evaluation datasets, measuring response accuracy, and identifying hallucinations and edge cases.

Build and own automated quality engineering for Tekion’s AI Platform, including APIs, SDKs, data and feature pipelines, model serving, deployment, LLM gateways, and vector stores. Design regression, performance, scalability, reconciliation, and reliability testing; validate ML data flows and platform SLOs; develop evaluation frameworks; use LLMs to accelerate test creation; and lead root-cause analysis and preventive improvements across platform and infrastructure teams.

Provides technical leadership for designing and building scalable, high-performance software systems. Leads complex engineering initiatives, designs distributed system components, partners with product and cross-functional teams, promotes engineering best practices, mentors developers, and resolves system-wide issues through root cause analysis. The role requires strong expertise in cloud-native development, containerization, scalability, fault tolerance, observability, and large-scale application delivery.

Own full-chip physical verification and signoff for advanced GPU and SoC designs from block assembly through tapeout. Responsibilities include DRC, LVS, antenna verification, 3D die-stacking validation, advanced-node signoff, AI-powered automation, flow development, and cross-functional design closure. Requires expertise in physical design verification, VLSI concepts, signoff tools, and RTL-to-GDSII implementation processes.

Develop and integrate advanced camera features within the Android framework and Qualcomm CamX Stack. Optimize camera performance and image processing, troubleshoot camera-related issues, and implement ML models in camera pipelines across DSP and GPU platforms. The role requires expertise in Android camera APIs, CamX feature implementation and debugging, image processing, multimedia frameworks, C++, threading, and performance tuning.

Defines and governs the end-to-end technology strategy, architecture roadmap, standards, and design governance for PCS Digital applications. Provides senior technical authority across cloud-native architecture, cybersecurity, reliability, observability, lifecycle management, modernization, and operational readiness. Partners with product, engineering, clinical, regulatory, quality, and service stakeholders to align architecture with customer, patient safety, compliance, and business needs. Mentors senior technical leaders and influences enterprise decisions without direct reporting authority.

Leads the long-term architecture and technical strategy for Uber’s Rider mobile applications, client platforms, edge capabilities, and backend services. Establishes standards for performance, reliability, testing, observability, build systems, and release quality. Builds reusable frameworks and developer tools, leads major migrations, defines client-server contracts, and drives complex cross-organizational initiatives. Influences senior stakeholders and enables multiple engineering teams to deliver scalable, high-quality rider experiences.

Leads validation strategy and automated testing for NAND-based SSD firmware across functional, performance, reliability, interoperability, and customer qualification domains. Develops test plans and automation frameworks, debugs NVMe and SAS issues, analyzes quality risks, and drives issue closure with cross-functional engineering teams and hyperscale customers. Applies AI and machine learning to test generation, failure analysis, anomaly detection, reporting, and predictive quality. Mentors engineers and leads complex validation programs.

Owns architecture for Swiggy’s high-scale ordering, checkout, pricing, assortment, and fulfillment platforms. Leads technical vision, distributed systems design, production operations, incident response, cost and performance optimization, developer platforms, cross-company integrations, and applied ML/GenAI architecture. Requires hands-on coding, end-to-end lifecycle ownership, and technical leadership across complex, high-throughput consumer systems.

Leads, hires, mentors, and develops software engineering teams while providing technical direction and architectural oversight. Drives delivery of scalable back-end, full-stack, platform, integration, data, and AI-enabled systems. Partners with product, architecture, program management, and data teams to establish roadmaps, remove blockers, improve engineering practices, and ensure reliable production operations through CI/CD, observability, testing, security, and incident management.

Lead development of ARM-based SoC subsystems using Cadence design, verification, and emulation platforms. Build and port systems to Palladium and Protium, ensure functional correctness, analyze hardware-software performance, and recommend improvements. The role requires deep RTL development and verification experience, expertise in AMBA and CHI protocols, SoC integration knowledge, and emulation experience. Familiarity with PCIe, CXL, and automated integration and verification methodologies is beneficial.

Develop and ship Yahoo Mail mobile features for Android, owning projects from technical design through deployment, monitoring, and improvement. Build scalable solutions using Kotlin, Java, Android frameworks, Jetpack Compose, and React Native; integrate APIs; address performance, reliability, and usability challenges; conduct code reviews; collaborate cross-functionally; mentor teammates; and use AI development tools to improve engineering productivity while maintaining quality and security.

Leads architecture and development of a cloud-based, multi-tenant network management platform. Responsibilities include building AI/ML network analytics, enterprise integrations, high-throughput telemetry processing, zero-trust security, APIs, edge gateways, scalable distributed systems, and hybrid cloud solutions. The role mentors engineering teams, establishes software development practices, optimizes performance, and works with enterprise customers on complex integrations. Requires extensive software development and network management experience, strong networking expertise, and knowledge of major network vendors.

Leads architecture and hands-on development of secure, scalable, cloud-native enterprise applications, emphasizing backend services and distributed systems. Owns technical initiatives from design through production, drives testing, observability, CI/CD, reliability, security, and cost optimization, and applies AI/ML capabilities. Provides technical leadership, mentorship, architectural influence, and cross-functional collaboration across engineering, product, business, and platform teams.

Leads architecture and hands-on development of scalable, secure, cloud-native enterprise applications, primarily backend services across the full stack. Owns complex initiatives from design through production, drives testing, observability, CI/CD, reliability, security, and cost optimization, and applies AI/ML and generative AI capabilities. Provides technical leadership, mentorship, architectural influence, and cross-functional collaboration.

Lead RTL-to-GDS physical design methodology for high-performance CPU cores at advanced TSMC N3 and N2 nodes. Architect automated, ML-driven flows to optimize power, performance, and area; define hierarchical floorplanning and integration strategies; partner with EDA and IP providers; build scalable flow automation, dashboards, and execution systems; and guide early PPA modeling and timing, IR drop, electromigration, and crosstalk closure.

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.

Build scalable, low-latency backend APIs, event-driven services, integration layers, and microservices supporting personalization and recommendation experiences. Partner with AI/ML and data engineers to deploy models, expose AI services, and develop React applications. Improve security, observability, reliability, performance, scalability, and operational efficiency while using AI-assisted engineering tools to enhance delivery and code quality.