Top Machine Learning Jobs in India

Seeking an AI/ML Engineer to enhance RAG systems, design BERT models, and utilize Pinecone for scalable solutions, collaborating with cross-functional teams.

Develop machine learning models and collaborate with teams to translate business needs into analytical solutions, ensuring model performance and data quality.

Lead the end-to-end data science pipeline, develop AI/ML models, collaborate with engineering teams, and engage business users to translate complex problems into solutions.

As a Senior AI and ML Engineer at NVIDIA, you'll build insights into AI tools, develop testing environments, and automate workflows, enhancing productivity for software development and DevOps.

As a Full Stack Machine Learning Engineer, you will develop AI-powered applications, integrate ML models, and collaborate with cross-functional teams to deliver impactful solutions.

Develop and implement AI Copilot use cases for IT and cybersecurity teams, conduct research on GenAI technologies, and design scalable microservices.

The role involves designing and optimizing AI/ML products, building conversational interfaces, managing AI pipelines, and collaborating with other teams to enhance user experiences.

Design and implement machine learning models and algorithms, collaborate with data scientists and software engineers, and deploy models into production environments.

As a Machine Learning Engineer, you will design and implement ML capabilities, perform data analysis, and collaborate on ML solutions.

Lead the design and implementation of ML capabilities for Autodesk's RAG platforms, providing mentorship, collaborating with stakeholders, and delivering solutions to business challenges.

As a Senior Machine Learning Engineer, you'll build LLM-powered agents, collaborate on experiments, support prompt engineering, and monitor AI features in production.

Develop AI-driven solutions for cybersecurity, focusing on machine learning pipelines, cyber threat detection, and mitigation of cyber-attacks like ransomware.

As a Senior Machine Learning Platform Engineer at Roku, you will design and scale ML systems for personalized content recommendations, focusing on robust service development and collaboration with cross-functional teams.

As an AI/ML Data Scientist, you will design and deploy generative AI models, analyze and generate human-like text, and deliver impactful AI products.

The Machine Learning/Data Engineer applies machine learning and statistical analysis to solve business problems, processes large datasets, writes efficient Python code, and mentors junior developers.

The Machine Learning Engineer will design and maintain ML systems, build APIs, develop backend features, and collaborate with cross-functional teams to enhance ML workflows and monitor model performance.

As a System Administrator, you'll manage systems data, provide solutions and compliance, and enhance customer success in various sectors.

Develop clean and efficient backend components in Python, maintain existing systems, collaborate with team members, and conduct code reviews.

As a Staff Software Engineer, you will lead projects, drive technical standards, and build accessible AI/ML tools on the Gradient Platform using various technologies.

Design, develop and implement machine learning models to solve complex issues, collaborate with teams on ML solutions, and ensure model deployment and performance monitoring.

Design and develop web applications using C# and ReactJS. Mentor junior developers, ensure code quality, and collaborate with various teams. Optimize performance and maintain technical documentation.

The MLOps Engineer will develop and maintain ML infrastructure, automate deployment workflows, test models, and ensure regulatory compliance in healthcare applications.

The Sr ML Engineer will lead the design, development, and deployment of ML models, collaborate with stakeholders, and mentor junior engineers.

Develop and deploy AI agents using Aisera's platform, integrate with external systems, and provide technical support for successful implementations.

Assist in building scalable data workflows, support AI/ML projects, and contribute to mentor-led development and research on GCP features.