Top Machine Learning Jobs in Bangalore

Create and review realistic, domain-specific robotics tasks in Hindi; apply scoring rubrics; evaluate AI and human responses for accuracy, regulatory alignment, and professional quality; and produce gold-standard solutions and expert feedback.

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

Design, develop, operate, and integrate Nike's multi-cloud platform solutions. Lead technical priorities, define engineering best practices, build observability, implement cloud infrastructure using Kubernetes and autoscaling, and collaborate with cross-functional partners to translate business needs into technical solutions.

Lead a cloud infrastructure engineering team to design, build, operate, and govern Nike's multi-cloud platform. Split time between hands-on architecture, development, and automation, and leadership duties including technical strategy, best practices, cross-functional collaboration, mentoring, and translating business needs into cloud solutions.

Lead a cloud infrastructure engineering team building and operating Nike's multi-cloud platform. Split time between hands-on design, development, and operations of cloud solutions and leadership duties: setting technical priorities, defining best practices, coaching engineers, and partnering with cross-functional teams to deliver scalable, secure cloud architectures.

As a Staff Software Engineer, you will develop and scale ABBYY's AI platform, focusing on Kubernetes, DevOps, and MLOps while mentoring engineers and designing systems.

The Staff Software Engineer will enhance and optimize the NetSuite ERP system, collaborating with stakeholders to analyze requirements, develop solutions, and implement advanced integrations leveraging AI and automation.

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 development and operation of Nike's multi-cloud access, entitlement, governance, and cost-optimization platform. Drive architecture, roadmap, squad leadership, SLO-driven operations, AI-assisted automation, and cross-region co-ownership while mentoring engineers and ensuring reliable, secure management plane services.

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

The Senior Software Engineer will design and maintain backend software, APIs, and collaborate with various teams to enhance product offerings and scale services.

Lead and manage a team of ML engineers, drive AI service delivery, and oversee production model deployment while fostering a high-performance culture.

The Analog Layout Engineer will create and optimize physical layouts for IC designs, applying AI/ML tools and collaborating with engineers on simulations and verification.

The ML QA Lead ensures quality in Cerebras software across ML workloads, focusing on testing accuracy, performance, and usability. Responsibilities include driving software quality, automating workflows, debugging issues, and collaborating across teams.

Design and optimize scalable data pipelines, maintain data models, ensure data quality, and collaborate with ML engineers. Mentor junior engineers.

Responsible for the end-to-end design, development, and deployment of Machine Learning models, collaborating with teams, and managing deployment lifecycles.

As a Software Engineer for Middle Office Systems, you will develop AI-enabled trading services, optimize system performance, and mentor junior engineers while collaborating with other teams.

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

The Associate Systems Developer will support application development and maintenance activities, requiring programming in C#, and working with .NET technologies and Azure DevOps.

The AI/ML Data Engineer will develop and maintain data pipelines, integrating diverse data sources and ensuring data quality while utilizing automated and scalable data solutions.

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 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.