Top Machine Learning Jobs in India

The Implementation Associate supports the Professional Services team by assisting in the implementation of software solutions. Responsibilities include coordinating customer onboarding and setup, managing project timelines, maintaining documentation, and providing feedback for continuous improvement.

The Partner Success Specialist will assist in onboarding customers into ResMed's partner ecosystem. Responsibilities include organizing partner meetings, managing contracts, supporting the Partner Onboarding team, updating Salesforce, and maintaining communications with stakeholders to ensure successful onboarding and customer activations.

As a Staff Machine Learning Engineer, you will design and maintain robust infrastructure for deploying and monitoring machine learning models. Collaborate with data scientists, implement CI/CD pipelines, ensure security and compliance, and optimize model performance while documenting processes and guiding team members.

As a Software (ML Product) Engineer at iterative.ai, you will enhance user workflows for DVC, collaborate with technical product managers, and improve MLOps practices within ML teams. Responsibilities include optimizing the tool’s usability and driving projects like dvclive, emphasizing software engineering skills and communication.

As a Research Scientist, you will innovate machine learning applications for customer experience, collaborate with AI researchers, develop technical roadmaps, integrate AI into products, and publish your findings.

As a Machine Learning Engineer at Pythian, you will focus on building and optimizing machine learning pipelines, deploying models to production, ensuring scalability and reliability, integrating machine learning models, and collaborating with cross-functional teams. Responsibilities include designing and maintaining ML pipelines, deploying models, optimizing performance, integrating with cloud platforms, implementing monitoring systems, and staying updated on ML advancements.

The VP of Global Fraud Management is responsible for leveraging data analytics and machine learning to improve operational efficiency and drive innovation, alongside developing predictive models for risk identification and strategic decision-making, while managing internal and external stakeholder relations.

The SW Systems Engineer will innovate and define user experience for AI-driven network management, leading the software development lifecycle to create data mining, machine learning, and networking solutions. Responsibilities include driving strategic innovation, conducting design and code reviews, and deploying high-performance systems.