Top Machine Learning Jobs in India

Lead brand and pipeline analytics within a Value Team to deliver advanced analyses (segmentation, adherence, HCP network, patient flows), provide actionable insights, standardize reporting, manage analytics projects and vendors, drive continuous improvement and capability building, and ensure compliance while working in an agile, cross-functional global environment.

Partner with cross-functional value teams to deliver omnichannel analytics for oncology: design and execute advanced analytics (campaign measurement, ROI, optimization, NLP/ML), consult on campaign measurement, automate reporting, manage projects and vendors, and provide actionable insights to inform brand and investment decisions.

Lead omnichannel analytics for oncology brands: design and execute advanced analytics (campaign measurement, ROI, optimization, NLP/ML), partner with stakeholders and agencies, standardize reporting, manage projects and vendors, and deliver actionable insights to inform brand and pipeline decisions.

Partner with cross-functional Value Teams to deliver omnichannel analytics: campaign measurement, ROI, tactic optimization, and model-driven recommendations. Lead analytics projects, ensure data integrity and tagging, work with media agencies, automate reporting, mentor teammates, and drive analytic capability and continuous improvement within an agile framework.

Drive brand and pipeline analytics to deliver actionable insights. Execute advanced analytics (segmentation, adherence, HCP network analysis, patient flows), automate reporting, manage projects, and collaborate cross-functionally within an agile Value Team to support commercial and pipeline objectives.

Develop and implement ML algorithms for finance, enhance model accuracy, design cloud solutions, and build MLOps pipelines. Collaborate with data scientists and engineers while staying updated on AI trends.

The role involves designing AI/ML solutions, aligning them with business strategies, and leading a team in developing applications. Responsibilities include monitoring technology trends, prototyping AI techniques, and managing vendor interactions.

As a Sr. Engineering Manager, you will lead a team of full stack engineers in developing innovative robotics solutions, focusing on team management, technical decision-making, and product development operations. You will also influence product roadmaps and resolve technology roadblocks while ensuring adherence to development standards.

Design, build, and deploy production AI/ML solutions on Snowflake and AWS. Develop LLM, NLP, and computer vision models, implement MLOps, integrate systems, follow governance (NIST, GDPR/CCPA), and collaborate with stakeholders to deliver measurable business value.

Work as a Machine Learning Engineer on innovative products, utilizing frameworks like Pytorch and PySpark, researching models, and developing scalable solutions.

Seeking an AI-ML Technical Architect to design, develop, and deploy scalable models on Azure. Requires deep expertise in AI/ML, big data tools, MLOps, and Python.

The Supply Chain Analyst ensures production continuity by providing insights into supply chain risks, validating supplier data, and developing mitigation strategies while managing data workstreams and collaborating across functions.

The role involves leading data science initiatives, mentoring team members, deploying models, and ensuring high-quality technical solutions. Responsibilities include coding, architecture design, and client requirement translation.

The role involves leading AI and ML strategies, integrating advanced capabilities into products, and optimizing data science models, emphasizing innovation and reliability.

Develop methodology, flows, and tools for SoC and IP development efficiency; work with teams on automation tools using VLSI expertise.

The Architect - Machine Learning leads AI/ML architecture design, innovation in GenAI technologies, and oversees ML deployment strategies while mentoring teams and integrating solutions with enterprise systems.

The Machine Learning Engineer will build and deploy agents using various platforms, design interaction patterns, and collaborate with stakeholders to define requirements and drive adoption of best practices.

The role requires developing scalable AI/ML solutions using Azure, integrating GPT models, overseeing coding standards, and mentoring teams.

Lead the architecture of physical implementation for high-speed CPU designs, focusing on automated ML-driven methodologies and PPA optimization, while interacting with EDA partners.

In this role, you will develop and maintain ML-focused applications, collaborate with data scientists, and build data pipelines for scalable AI workloads.

Designs, develops, and deploys production-ready AI/ML solutions using cloud AI services (especially AWS AI Services). Acts as an SME, leads and mentors teams, engages stakeholders, and ensures models deliver measurable business value.

The AI / ML Engineer develops applications that utilize AI tools and cloud services, ensuring quality and production readiness while working with Generative AI technologies.

Design and implement production-ready AI/ML applications using LLMs and cloud AI services. Lead and mentor teams, make technical decisions, deploy models (chatbots, image processing, deep learning), and optimize pipelines for performance and quality.

As an AI/ML Engineer, you'll develop applications using AI tools and cloud services, focusing on production quality and various AI models involving deep learning and chatbots.

Develop applications utilizing AI tools and cloud services, focusing on generative AI models, deep learning, and collaboration with teams to solve technical challenges.