Top Machine Learning Jobs in Bangalore

Leads the design and implementation of automated testing frameworks for web, mobile, API, and performance testing. Collaborates with development and QA teams on automation strategies, maintains test scripts and documentation, reviews code, analyzes defects, and supports manual testing. Mentors junior engineers and evaluates testing tools. Requires Java or Python, API testing, SQL, SDLC, Agile/Scrum, test lifecycle, version management, and test management experience. CI/CD, ML testing, performance testing, BDD, cloud, and data lake testing are preferred.

The Engineering Manager leads the NIRA team, executing the engineering roadmap and improving engineering practices while managing a high-performing team.

Architect system-level SoC platforms across product tiers: define architecture specs, hardware/software partitioning, KPIs, and IP requirements. Collaborate with cross-functional teams through design and productization, perform make-vs-buy and performance/power/area tradeoff analyses, and ensure compliance with automotive safety and mixed-criticality standards.

Manage engineering teams, focusing on recruitment, training, project management, and technical decision support while promoting a strong engineering culture.

Lead development and innovation of managed switching solutions targeting SMEs, focusing on product features, cost-performance, technical architecture, and market-driven solutions.

Drive technical direction and build end-to-end onboarding and adoption experiences across frontend and backend. Design, operate, and optimize REST and GraphQL APIs, integrate data pipelines and ML/AI features, ensure scalability, security, observability, and developer productivity, mentor engineers, and collaborate with cross-functional and distributed teams.

Support aeroacoustic integration across aircraft design stages by evaluating noise sources and propagation, defining requirements, developing methods and technologies, monitoring noise during development, and collaborating with multidisciplinary teams to meet aircraft noise and performance targets.

Lead resolution of complex, cross-system incidents by troubleshooting ambiguous production issues, performing root cause analysis, automating workflows, improving observability and reliability, coordinating specialists, and mentoring engineers to reduce toil and improve operational processes.

Develop and maintain scalable full-stack software applications with emphasis on reliability and performance. Integrate AI and machine learning features, build network automation solutions, and implement event-driven real-time data pipelines. Collaborate with designers, product managers, and engineers in agile development. Manage CI/CD processes, conduct code reviews and automated testing, document solutions, and uphold security, quality, and maintainability standards.

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.

Lead and develop engineering managers across multiple teams, own org design and multi-quarter engineering strategy, ensure delivery/operational health, drive resourcing and budget decisions, represent engineering in senior cross-functional forums, and build a leadership pipeline for a large-scale consumer product organization.

Design and develop secure, scalable full-stack systems for fraud prevention and financial crime compliance. The role involves building cloud-native microservices, contributing to fraud screening platforms using streaming and machine learning, collaborating with product and business teams, managing platform operations, maintaining documentation, and mentoring junior engineers. Candidates will lead complex engineering initiatives, work with distributed systems and high-availability platforms, and use technologies including Java, Spring Boot, AWS, Kafka, Terraform, and REST APIs.

Designs, builds, delivers, and maintains software applications and services. Develops Java and Spring Boot enterprise applications, RESTful APIs, and frontend features using React or Angular. Manages relational databases, Redis caching, Docker containers, Kubernetes deployments, and AWS EKS infrastructure. Applies software development lifecycle practices, CI/CD, testing, documentation, performance evaluation, data structures, and algorithms. Collaborates in Agile environments and contributes to innovation and production integration of emerging technologies.

Own moderately complex customer engagements from configuration and integration through deployment and incident response. Build AI-enabled solutions, automation, reusable integration patterns, documentation, and operational runbooks. Troubleshoot customer issues, assess technical risks, coordinate with internal teams, and mentor newer Customer Engineers. The role requires autonomy, strong customer communication, enterprise platform expertise, and hands-on experience with APIs, integrations, and deployments.

Partner with semiconductor customers to drive RTL-to-GDSII implementation on advanced nodes, develop methodologies, debug tool issues, deploy ML productivity solutions, influence product direction, collaborate with sales and mentor AE teams.

Lead backend platform engineering for Horizon 8 VDI: design and implement scalable microservices, APIs, and platform artifacts (OVA/VM/container). Improve Kubernetes and CI/CD processes, debug distributed systems, mentor engineers, collaborate cross-functionally, and own architecture, performance, and reliability.

Develop and maintain automated tests and in-house frameworks (C#/Selenium); use AI-assisted testing and basic ML insights for test generation and analysis; detect, log, and troubleshoot defects; maintain test scripts, procedures, and test artifacts; collaborate with teams on root cause analysis.

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.

Design, develop, and maintain scalable Python-based automation test frameworks and tools for automotive infotainment. Integrate GenAI and ML to enhance test coverage, implement CI/CD for cloud testing, create reusable test components, analyze test results, collaborate with dev/QA/DevOps, and drive continuous improvement in automation processes.

Design, develop, test, deploy, and maintain RPA solutions using Automation Anywhere. Gather requirements, document processes, create scalable bots, perform QA, troubleshoot issues, and train end-users while collaborating with stakeholders.

Lead engineering teams in developing complex software applications, enhance user experiences, and oversee migration to microservices.

The Product Technical Lead at Airbus guides a team in designing and executing digital product development, focusing on AI/ML, data engineering, and the overall data strategy. Responsibilities include leading LLM development, ensuring code quality, and implementing CI/CD pipelines.

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.

Build modular, API-first tooling and web applications for Nike's Consumer Product & Innovation teams. Design and implement cloud-native services (AWS), front-end SPA integrations, CI/CD pipelines, and automated tests. Collaborate with engineers, product managers, and cross-functional partners to deliver scalable software solutions.

Build modular, API-first internal tooling for product creation teams. Design and implement cloud-native services and modern web frontends, collaborate with product and engineering leads, and ensure testing, performance, and architectural best practices.