Top Machine Learning Jobs in India

As an AI Infrastructure Architect, design and develop AI infrastructure and hardware solutions while optimizing performance, cost, and scalability.

The Data Engineer is responsible for designing, developing, and maintaining data solutions, ensuring data quality, and implementing ETL processes. Collaboration across teams to optimize data workflows and mentoring junior members is essential.

The AI Infrastructure Architect designs and develops AI infrastructure, optimizes performance and evaluates technologies for better scalability. They lead vendor evaluations and integrate solutions across teams while mentoring junior staff.

As an AI/ML Engineer, responsibilities include developing AI applications, integrating cloud services, and leveraging generative AI models for scalable solutions. Collaboration and technical documentation are key aspects.

Design and structure advanced language models, analyze performance, collaborate with teams, and mentor junior members in machine learning applications.

The ML Engineer will develop and maintain software solutions for Machine Learning projects, focusing on code scalability, model deployment, and documentation, while collaborating with cross-functional teams.

Design and implement automation solutions using Microsoft Copilot and Power Platform, optimize workflows, collaborate with stakeholders, and ensure compliance and governance.

Design and develop analog integrated circuits, utilizing AI/ML tools. Collaborate with teams, conduct simulations, and drive innovation in circuit design.

As a Senior Engineer in Data & ML Platform, you will build ML pipelines, design scalable data platforms, and collaborate with teams on ML solutions to support business decisions.

As a Sr. Engineer, you'll design and maintain a scalable Data & ML platform, facilitating ML pipelines, collaborating with cross-functional teams, and building tools for data preparation, feature engineering, and model training.

This role involves designing, building, and scaling a Data+ML platform, collaborating on machine learning pipelines, and incorporating cloud services for deployment and execution.

Lead and mentor a data science team, develop ML solutions, drive AI/ML initiatives, ensure model performance and fairness, and foster innovation.

The role involves architecting LLM applications, designing RAG pipelines, optimizing models, developing APIs, and collaborating with teams to enhance Crunchyroll's services.

The Forward Deployed Engineer is responsible for designing, developing, and deploying agent-based AI solutions using the Workato platform, collaborating with cross-functional teams and ensuring efficient AI workflows for enhanced IT operations.

Lead the ED&A delivery function ensuring high-quality execution of data integration and analytics projects while managing teams and strategic initiatives.

The Sr Advanced Data Scientist will lead complex data science projects, provide mentorship, and contribute to the team's strategic vision by applying machine learning and statistical modeling expertise.

Lead the effort to design, build, and configure applications, acting as the primary point of contact and managing the team for successful project delivery.

Design, develop, and enhance chatbots and voice bots utilizing Google Dialogflow CX and Google Cloud technologies, focusing on conversational AI solutions and backend integrations.

Design and develop chatbots using Google Dialogflow, Python, and machine learning techniques, ensuring they integrate seamlessly with backend systems and provide intelligent user interactions.

The Google DialogFlow Engineer will develop and enhance chatbots and voice bots using Google Cloud technologies, focusing on Dialogflow CX and integrating advanced AI capabilities.

The role involves designing, developing, and deploying chatbots and voice bots using Google Cloud Platform and Dialogflow CX, optimizing performance, and integrating backend systems.

The Google DialogFlow Engineer will design and enhance chatbots and voice bots, utilizing Google Cloud technologies, focusing on Dialogflow CX, LLM capabilities, and backend integrations.

The Google DialogFlow Engineer will design, develop, and enhance chatbots and voice bots using Google Cloud technologies, focusing on Dialogflow CX. Responsibilities include API integrations, natural language processing, and performance optimization, while collaborating with various stakeholders to meet user expectations.

The Google DialogFlow Engineer will design and develop chatbots and voice bots, optimizing conversational AI solutions using Google Cloud technologies and integrating them with backend systems.

Design and develop chatbots using Google Dialogflow CX and Python, optimizing AI capabilities for conversational experiences, and integrating with backend systems.