Top Machine Learning Jobs in India

The Data Scientist will develop predictive models and AI solutions, collaborate with cross-functional teams, and build scalable pipelines while ensuring model accuracy and reliability.

The role involves leading product strategy and development for balance sheet management solutions using AI and analytics, collaborating with senior stakeholders, and mentoring teams in product management best practices.

The role involves leading balance sheet management product strategy, utilizing AI and machine learning to develop data-driven tools and analytics, and overseeing product lifecycle while collaborating with senior leaders across finance and technology.

Lead AI/ML Engineer responsible for developing and implementing machine learning solutions, managing teams, ensuring compliance, and driving innovation in healthcare applications.

The role involves maintaining and optimizing ML infrastructure, diagnosing complex issues, performing system optimization, and collaborating with engineers to resolve workflow issues.

Lead the development of AI-driven solutions, innovate, and implement strategies in machine learning, mentor scientists, and collaborate across functions.

The Senior QA Engineer will develop and maintain automation frameworks using Java, Selenium, and REST Assured, focusing on AI integration and data validation for effective testing.

The Senior Scrum Master will ensure effective Scrum practices across teams, enhance team efficiency, facilitate Scrum ceremonies, and manage impediments in AI and Data Science environments.

Responsible for generating new revenue by opening new accounts in the mortgage industry, driving pipeline creation, and closing enterprise deals.

The Engagement Manager will drive business analytics for CPG clients, leading workshops, managing cross-functional teams, and developing consulting frameworks while liaising with senior stakeholders.

The Engagement Manager will drive business-analytics execution, lead client workshops, develop strategic recommendations, manage client relations at a senior level, and contribute to organization building through mentoring and training.

The Principal Software Engineer will define architectural strategy, solve complex technical challenges, mentor teams, and guide future platform development at Loop AI.

The role involves developing and automating applications in the automotive industry, providing customer support, leading application development, and collaborating with various teams to implement solutions.

The Senior Data Engineer will collaborate on software projects within Nike, focusing on building data tooling and supporting the Consumer Product team. Responsibilities include leading engineering efforts, coordinating with teams, mentoring juniors, and developing API-first solutions.

The role involves developing competitive intelligence, responding to RFPs, collaborating with engineering, ensuring regulatory compliance, and enabling partners in the cybersecurity domain.

Lead the design and implementation of scalable architectures for CloudSEK's platform, guiding a team of engineers and ensuring code quality and security.

The Data Scientist will analyze and model data for ML systems, focusing on Personalization and Recommendation Engines, and collaborate with teams to enhance data-driven solutions.

The Director will lead a team of Data & AI specialists, overseeing technical support and ensuring successful customer operations on the Databricks platform.

As an ML Engineer, you will design, experiment, and deploy AI/ML models, evaluate their performance, and leverage Python and SQL.

The Senior Director will lead K2View's global partnerships, drive pipeline growth, and design go-to-market strategies with GSIs and technology partners.

Lead and develop software engineering projects focusing on Python code, database design, and RESTful APIs while collaborating across teams to ensure quality software delivery.

Lead data science initiatives, designing cutting-edge AI solutions, mentoring teams, ensuring responsible AI practices, and advancing business objectives through data insights.

Responsible for leading a team in developing AI applications utilizing ML and NLP techniques, focusing on generative AI and data analysis solutions.

Lead development and productionization of LLM and GenAI solutions using LangChain, fine-tuning, and RAG. Write PEP8-compliant Python, containerize with Docker, ensure production-quality code and testing, apply ML/DL methods (e.g., XGBoost, K-means), and support deployments via terminal and version control.

Lead design and delivery of production-grade AI/ML solutions for healthcare, focusing on NLP/LLM, RAG, time-series forecasting, model lifecycle management, deployment, optimization (quantization), and mentorship of engineering teams.