Top Machine Learning Jobs in India

The Applied AI ML Associate Sr role involves designing and delivering software solutions, developing algorithms for data analysis, and enhancing systems through machine learning. The position requires overseeing data analysis, coding, and ensuring quality in production systems.

The Senior Software Engineer will focus on optimizing and evolving the data platform to solve complex data challenges. Responsibilities include contributing to the data platform roadmap, collaborating with engineers across various disciplines, innovating ETL processes, and mentoring team members.

As a Product Manager for Machine Learning & Intelligence Operations, you will lead AI-driven customer service innovations, define product strategy and roadmap, and collaborate with cross-functional teams to enhance customer experience. Responsibilities include managing product features, analyzing customer journeys, and prioritizing product enhancements while fostering a culture of innovation.

As a Lead Data Scientist focused on Generative AI, you will lead data science initiatives to build innovative applications in employee engagement, design intelligent systems, define key metrics, and develop Big Data processing systems using machine learning techniques.

The Data Scientist at PitchBook will leverage machine learning and cloud technologies to research private markets and improve platform navigability. Key responsibilities include data analysis, model development, and optimization, along with enhancing decision-making through insights derived from data.

As a GenAI Architect, you will lead projects focused on AI solutions, provide technical guidance on ServiceNow technologies, and drive customer value realization. Your role includes hands-on delivery of capabilities, collaboration with cross-functional teams, and contribution to thought leadership in GenAI offerings.

The role involves working on AI products and client solutions using machine learning engineering and data science tech stack. Key responsibilities include designing ML platforms, building advanced ML pipelines, collaborating with data scientists to create AI models, managing the complete ML lifecycle, and mentoring team members.

The role involves working on AI products and client solutions, developing GenAI applications, collaborating with data scientists to design AI models, building ML platforms, and managing the ML lifecycle. The Specialist will also lead a team, mentor talent, and ensure technical robustness through design and code reviews.

The role involves designing and building a scalable ML Experimentation Platform. Responsibilities include modularizing ML code, establishing model development patterns, and leveraging cloud services for efficient execution of data pipelines while collaborating with data scientists and engineers.

The Managing Principal – Data Governance leads projects in data governance, strategy, and analytics, focusing on transforming financial services. Responsibilities include managing business and technical teams, developing relationships with clients, and executing data programs across various sectors.

This role involves leading data governance initiatives, managing business and technical teams, and delivering analytic and data science projects within the financial services sector. It requires expertise in data strategy, management, and emerging AI concepts, as well as active collaboration with clients and stakeholders.

Lead Credit and Data Science functions for international markets. Develop risk models, credit policies, and innovative products to enhance customer experience and business growth. Collaborate with teams to adapt strategies based on market-specific data and consumer behavior.

As a Staff Data Scientist at Empower, you will develop risk models and credit policies to drive competitive underwriting practices. You will lead teams to analyze consumer behaviors and adapt solutions for the Latin American market, enhancing customer financial well-being. This role is pivotal for launching innovative financial products and requires tackling complex geographic challenges.

As a Fraud Modeling - Machine Learning Associate, you will develop and implement machine learning models and statistical models for risk management. This role involves leveraging big data and cloud computing platforms to create innovative modeling solutions, collaborating with various departments, and effectively communicating results to management.

As the Lead Machine Learning Engineer at Capital One India, you will design and build data-intensive solutions, automate governance within the ML development lifecycle, and collaborate with cross-functional teams to enhance machine learning applications and data pipelines.

The Principal Associate - Machine Learning Engineer will lead the design and implementation of observability tools, enhance observability capabilities using Generative AI models, build core APIs for observability of models, and drive the adoption of emerging technologies. The role demands a research mindset to showcase capabilities of large language models for production solutions.

As a Senior Lead Machine Learning Engineer at Capital One, you will architect and develop full-stack solutions for monitoring and managing Generative AI and machine learning models, collaborate with teams to build observability platforms, and leverage cloud technologies to enhance insights into model performance and compliance.