Top Machine Learning Jobs in Bengaluru

As a Machine Learning Scientist - Natural Language Processing (NLP) - Senior Associate, responsible for developing state-of-art ML models, collaborating with various teams, and deploying solutions into production. Required expertise in Deep Learning and classical ML techniques. Hands-on experience with virtual assistant model development and optimization. Strong analytical thinking and communication skills are essential.

As a Principal Engineer on the ITSM team, you will work on AI and ML algorithms to enhance IT Operations, reduce incident response times, and lead engineering projects. Your role involves collaborating with cross-functional teams to innovate and improve IT service management through machine learning techniques, while ensuring high software performance and reliability.

The Senior AI/ML Engineer will advise on data science activities, lead Gen AI use cases, design and implement MLOps pipelines, and automate ML tasks. Responsibilities include model development, data quality monitoring, and project management in collaboration with various stakeholders.

As a Senior Product Backend Engineer at Instabase, you will design and develop scalable backends, handle real-time data processing, collaborate with frontend engineers on API design, and improve platform stability. You will work directly on user-facing products that leverage AI and machine learning technologies.

As a Senior Machine Learning Engineer on the Recommendations team at Roku, you will develop advanced algorithms for personalized content recommendations and analyze business KPIs through online testing. You will work collaboratively to shape the ML ecosystem while mentoring new team members.

The Software Engineer III will design and deliver technology products, develop software solutions, maintain production code, optimize ETL processes, conduct analyses on data, and contribute to software engineering practices while supporting machine learning implementations.

As a Distinguished Machine Learning Engineer, you will develop and enhance systems for model governance and observability. You'll collaborate with cross-functional teams to build scalable ML applications, manage data pipelines, and leverage cloud technologies. Responsibilities include integrating model metadata inputs and ensuring successful deployments of ML models.

As a Senior Machine Learning Engineer at Atlassian, you will develop and implement machine learning algorithms and train models to enhance AI functionality in Jira. Your role includes designing system architectures, conducting evaluations, and mentoring junior engineers to leverage AI for transformative results.

The Head of International Credit and Data Science will lead the analytics team, developing risk models and credit policies to drive underwriting strategies and innovative product launches in Latin America and South East Asia. The role focuses on leveraging data to enhance business growth and improve customer financial health, while adapting solutions for diverse markets.

The AI/ML Ops Engineer designs, builds, and deploys machine learning models, conducts model training and evaluation, implements them in production, collaborates with data scientists, monitors post-deployment performance for safety, ensures compliance with medical device regulations, and addresses patient privacy concerns.

The Managing Principal – Data Governance leads projects in data governance, strategy, and analytics, focusing on transforming financial services. Responsibilities include managing business and technical teams, developing relationships with clients, and executing data programs across various sectors.

This role involves leading data governance initiatives, managing business and technical teams, and delivering analytic and data science projects within the financial services sector. It requires expertise in data strategy, management, and emerging AI concepts, as well as active collaboration with clients and stakeholders.

Lead the development of ML infrastructure, providing technical leadership and mentoring to a team, ensuring high quality standards from model inception to deployment, and collaborating with data scientists for optimized data pipelines. Implement best practices for model versioning and evaluate model performance while maintaining industry standards.

The Machine Learning Engineer will develop and deploy machine learning models, collaborate with cross-functional teams, and enhance data-driven decision-making within the company. Responsibilities include utilizing AWS services, containerization technologies, and managing workflows to create production-ready ML systems.

As a Machine Learning Engineer, you will design and develop ML-powered capabilities to interpret vast amounts of log data. Responsibilities include validating ML opportunities, building scalable systems for data processing, and ensuring seamless collaboration to deliver solutions from concept to production.

As the Applied AI ML Director at JPMorgan Chase, you will lead the development of machine learning products, promote best practices, and drive innovation across teams. Your role involves creating ML assets, leading technical strategies, translating complex issues for leadership, and fostering a culture of diversity and inclusion.

The Senior Machine Learning Engineer at Bazaarvoice will develop AI/ML driven solutions using advanced techniques like natural language processing, mentoring junior engineers, and collaborating with product teams to optimize and create predictive models from large data sets.