Top Machine Learning Jobs in Bangalore

Early-career Performance Engineer in the Binance Accelerator Program. Perform hands-on performance testing and tuning, design AI-powered test strategies using LLMs and ML, build AI-driven anomaly detection and bottleneck analysis tools, research new AI technologies, and improve reliability of large-scale distributed systems.

The CAE Analyst is responsible for conducting structural and thermal analysis, fatigue life calculations, and solving complex FEA problems to support appliance product development at GE Appliances.

The Staff Engineer in Machine Learning will guide teams, solve client challenges, and enhance solutions leveraging their technical expertise.

The Enterprise Architect is responsible for designing AI-powered enterprise solutions and leading teams in implementing and deploying AI/ML applications across various environments.

Lead architecture and development of the core native iOS SDK and related apps. Own feature delivery from design to public release, write high-quality tested code, collaborate with R&D and ML teams, support customers to resolve issues, and manage priorities across large-scale, distributed projects.

Lead SRE for the Network Assurance Data Platform responsible for designing, building, and optimizing cloud and big-data infrastructure for ML/AI workloads. Provide technical leadership, troubleshoot production issues, implement SRE practices (monitoring, alerting, error budgets), mentor engineers, collaborate with cross-functional teams, and drive the platform roadmap and automation for enterprise-scale deployments.

Lead and manage a team of Software Engineers focusing on building tooling for internal teams at Nike, emphasizing collaboration and modern software practices.

The Director of Software Engineering will lead teams in developing highly available distributed systems, focusing on payment processing, AI solutions, and innovative capabilities, while ensuring product quality and team engagement.

Lead full lifecycle development of L2/L3 embedded RAN protocol stacks: design, coding, unit testing, debugging, and integration. Implement and enhance MAC/RLC features, analyze logs, debug in Linux, and support product releases. Apply AI/ML concepts for RAN optimization and develop/maintain solutions used by global customers.

Lead the architecture of physical implementation for high-speed CPU designs, focusing on automated ML-driven methodologies and PPA optimization, while interacting with EDA partners.

As a Python and Kubernetes Software Engineer, you will develop data analytics solutions using open source tools, collaborating with a distributed team.

You will design ML models to improve search and personalization, mentor junior engineers, and write maintainable code while collaborating with customers.