Top Machine Learning Jobs in India

The role involves developing AI-driven applications and chatbots using Python, overseeing quality of service, and managing performance metrics.

The Tech Project Manager will define and execute the vision for generative AI products, manage cross-functional teams, and oversee project lifecycles to enhance competitiveness and user experience.

As a Data Scientist, you will enhance data productivity, develop models, collaborate with business stakeholders, and provide insights to improve product usability and reseller performance.

As a PhD Quant Researcher, you will design, model, and deploy pricing and market microstructure models using machine learning techniques, impacting live trading systems.

The AI Engineer builds production-ready ML models and RAG systems for analyzing medical and insurance data while ensuring security and efficiency.

The Generative AI Intern will work on AI technologies, focusing on Python, machine learning fundamentals, LLMs, prompt engineering, and related frameworks.

As a Senior Data Analyst at Okta, you will analyze product data, build dashboards and reports, and communicate insights to stakeholders, leveraging SQL and advanced analytics techniques.

As VP of Software Engineering, you will manage product development, drive innovation, resolve complex issues, and collaborate with stakeholders to align product goals and execution.

The Principal Technical Support Engineer will solve customer issues, improve APM software, provide training, escalate problems, and conduct pre-sales consultations, requiring strong problem-solving and communication skills.

Lead the global HR systems strategy and operations, owning SAP SuccessFactors roadmap, integrations, AI-enabled HR automation, data governance, vendor management, multi-country rollouts, and leading HRIS analysts to drive adoption and efficiency.

Develop and maintain web and mobile applications, build and optimize AI/ML models, prepare and process data, collaborate with product teams to deliver AI-driven features, participate in code reviews, testing, and stay current with AI/Data Science advances.

Lead the development and deployment of AI/ML solutions, managing the entire model lifecycle and ensuring tangible business outcomes across various projects.

Develop machine learning algorithms to analyze brain data, design experiments, build data visualization tools, and assist in AI model development for education.

Partner with brand and pipeline Value Teams to deliver advanced analytics (segmentation, adherence, HCP networks, patient flows), produce actionable insights, automate reporting, manage analytics projects, mentor colleagues on statistical methods, and ensure compliance while working in an Agile environment to support commercial and medical affairs objectives.

Lead the global Omnichannel Analytics chapter to deliver advanced analytics and actionable insights. Set strategy, manage cross-functional delivery and agile ways of working, build team capabilities, oversee resource allocation, and ensure high-quality, compliant analytics outputs to drive commercial outcomes.

Partner-level analytics role within Brand/Pipeline Value Teams delivering advanced analytics (segmentation, HCP network, adherence, patient flows), actionable insights, standardized reporting, automation, and stakeholder recommendations. Collaborates cross-functionally, manages projects, mentors peers, and maintains proficiency with data systems (Redshift, Databricks, SQL, Python) to support pharmaceutical brand and pipeline strategies.

Deliver advanced brand and pipeline analytics (segmentation, adherence, HCP network, patient flows), generate actionable insights, automate reporting, manage projects, and collaborate with cross-functional global teams within an Agile Value Team.

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.

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.

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.