Top Machine Learning Jobs in Bengaluru

The Principal Associate in Machine Learning will lead the design and implementation of observability tools for generative AI platforms, utilising advanced analytics and machine learning. Responsibilities include building APIs and SDKs for observability, enhancing AI model performance, and driving innovative practices in ML governance.

As a Lead AI/ML Engineer, you will design, develop, and deploy advanced AI solutions, particularly focusing on natural language processing and machine learning techniques. Collaborating with product managers and mentoring junior engineers, you'll ensure high-quality production-ready code while aligning AI projects with business objectives. Your role encompasses the entire AI development lifecycle.

As a Senior Lead Machine Learning Engineer at Capital One, you will architect and develop full-stack solutions for monitoring and managing Generative AI and machine learning models, collaborate with teams to build observability platforms, and leverage cloud technologies to enhance insights into model performance and compliance.

As a Software Engineer III at JPMorgan Chase, you'll design and implement AI/ML solutions, optimize algorithms, and maintain production code. Responsibilities include analyzing data sets to drive improvements, producing architecture artifacts, and contributing to the software engineering community.

As a Risk Modeling - Machine Learning Associate, you will develop and implement machine learning and statistical models within the Consumer and Community Banking Risk Modeling team. Responsibilities include data manipulation, model development, quality testing, and collaboration with multiple teams to enhance credit risk models.

The Machine Learning Engineer II at Atlassian will build and scale machine learning models for business applications, utilizing expertise in Python or Java, and familiarity with SQL, Spark, and cloud environments. They will focus on practical solutions, communicate data science concepts effectively, and contribute to improving agent productivity using AI.

As an Analytics Solutions Manager - Applied AI/ML, you will lead the design and implementation of AI/ML solutions in the AWM Risk Management team, driving innovation and strategic alignment. Your responsibilities include developing scalable models, mentoring data scientists, and collaborating with cross-functional teams to integrate AI capabilities and enhance decision-making processes.

As a Senior Machine Learning Engineer at Atlassian, you will develop and implement cutting-edge machine learning algorithms, train complex models, and collaborate with teams to integrate AI features into Jira. Your role involves designing system architectures, conducting experiments, guiding junior engineers, and ensuring the practical application of AI within the product.

As a Senior Business Consultant in Data and AI Practice, you will drive AI consulting for Automotive, Manufacturing, and Healthcare sectors, leading complex projects and client engagement, while providing thought leadership and innovative solutions. You will collaborate with cross-functional teams, engage with clients, and manage end-to-end project delivery.

As a Lead Software Engineer, you'll design and implement end-to-end machine learning solutions, collaborate with teams to translate business requirements, create machine learning pipelines, and mentor junior associates. You'll ensure production-grade code and participate in firm-wide ML communities.

The ML Engineer Associate role involves executing and troubleshooting software solutions, designing and developing components, and analyzing data to improve application stability. This position emphasizes collaboration and learning in machine learning, coding, and system processes.

The Applied AI ML Lead will research and implement machine learning algorithms to enhance financial services. This individual will collaborate across teams, communicate complex findings, ensure regulatory compliance, and mentor junior associates while leading innovative projects.

The Principal Associate - Machine Learning Engineer will lead the design and implementation of observability tools, enhance observability capabilities using Generative AI models, build core APIs for observability of models, and drive the adoption of emerging technologies. The role demands a research mindset to showcase capabilities of large language models for production solutions.

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.

The Technical AI Evangelist will create documentation and code samples for Intel's AI technologies, engage with developers, promote AI solutions, and support customers in deploying AI solutions while staying updated on AI advancements.

The Architecture & Engineering Specialist for ML Engineering at ZS will design and build ML platforms, develop AI models, and manage the ML lifecycle while collaborating with data scientists and mentoring team members to achieve technical excellence.

The GCOA Enterprise Architect at Lilly is responsible for developing innovative technology solutions that enhance business productivity and efficiency. This role involves strategizing technology roadmaps, determining system architecture, aligning IT with business goals, and documenting processes through architectural models. The architect will work closely with stakeholders to ensure optimal technology usage and integrate emerging technologies into business processes.