Top Machine Learning Engineer Jobs in Mumbai

The intern will design and implement high-frequency trading algorithms, analyze market data for patterns, and develop tools for data analysis.

Lead the development and integration of AI capabilities into core applications using .NET Full Stack. Responsibilities include mentoring, designing scalable APIs, collaborating with teams, and ensuring code quality.

The ESG Client Success Operations Specialist will manage client engagements, enhance due diligence processes, support onboarding, and provide technical platform assistance while ensuring client satisfaction.

As an AI/ML Engineer, you will develop machine learning models, collaborate with teams, preprocess data, and optimize ML pipelines. Additionally, you will mentor junior members and contribute to AI/ML strategies.

Manage and mentor engineering teams, ensure high-quality product delivery, contribute to technical decisions, and enhance classroom learning experiences.

The Principal Product Manager leads product lifecycle management for brand safety solutions using ML/AI, ensuring effective collaboration and communication across teams.

Deliver compelling presentations and host discussions on emerging AI topics, engaging with senior leaders to translate AI concepts into strategic insights.

The Solutions Architect for AI/ML at Snowflake designs and deploys AI/ML solutions using Snowflake and its partners, ensures client success, and collaborates with internal teams while maintaining a hands-on approach.

The Data Operations Analyst develops custom product attribution based on client needs, utilizing tagging and machine learning; ensuring data mapping accuracy and project delivery.

The Senior Data Scientist will enhance the predictive modeling capabilities of Lyric's platform, focusing on machine learning and statistical methods for supply chain optimization.

Lead research initiatives focusing on customer AI experiences, conduct various research methodologies, and translate findings into strategic insights.

As a Senior Software Engineer II, you'll design APIs, improve performance, mentor engineers, and build AI solutions for better healthcare access.

Lead the development of machine learning products by driving technical direction, designing data pipelines, and collaborating with teams to innovate solutions in consumer finance.

The Senior AI/ML Data Scientist leads research and development of analytic solutions, builds data processing systems, and mentors associates.

The Field Application Engineer will serve as the primary technical contact for customers, focusing on implementing AI/ML hardware/software solutions, collaborating with teams, and ensuring customer success.

The Director of Data Engineering leads the development of data infrastructure, analytics models, and ensures compliance with data standards while leading a team to optimize healthcare operations.

As an Engineer I, you will develop high-quality software by gathering requirements, writing code, performing impact analysis, and managing testing phases.

The Associate Architect will lead the development and deployment of machine learning solutions on Azure, manage the ML lifecycle, and optimize existing models while providing technical leadership to project teams.

Drive the Search product roadmap at Bloomreach, focusing on AI, personalization, and data-driven decisions while ensuring customer engagement and market readiness.

As a Backend Software Engineer, develop and improve Bloomreach's multi-tenant search infrastructure, leveraging cloud technologies and machine learning for enhanced performance and scalability.

Lead the definition and delivery of AI-driven features and solutions. Translate complex needs into clear requirements, prioritize use cases, and coordinate cross-functional teams to deliver effectively.

The Data Science/Machine Learning Engineer will work with machine learning techniques, LLMs for NLP tasks, and data processing tools.

The ML Product Owner will shape the supply chain platform by developing forecasting capabilities, collaborating with teams to enhance decision-making using machine learning.

You will design and develop machine learning infrastructure and models, work with cross-functional teams, and build AI-driven applications, focusing on data scalability and performance.

Develop and deploy AI and ML models, collaborate with teams to design algorithms, and leverage data for insights and solutions.