Top Machine Learning Engineer Jobs in Mumbai

The Principal Machine Learning Engineer influences AI product development, collaborates with cross-functional teams, and drives business strategies using data analysis and insights.

The role involves developing AI solutions for banking operations, collaborating with cross-functional teams, managing code lifecycle, and ensuring code quality in the AIML space.

As a Software Engineer II, you will design and implement AI-driven software solutions, mentor engineers, and oversee project goals within a collaborative agile team.

As a Software Engineer III, you will design and deliver AI-driven software solutions, lead technical efforts, and collaborate across teams while mentoring others.

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

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.

The Lead-Information Security will manage data protection and security strategies, conduct risk assessments, develop compliance policies, and respond to security incidents while collaborating with various departments.

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.

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

Lead and innovate AI solutions by designing next-gen systems, collaborating on product development, and mentoring teams to enhance AI integration.

Lead technical design and architecture strategy for high-value digital solutions sales, collaborating with sales teams to present solutions and ensuring technical integrity during proposals.

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.

Lead innovation and analytics in research, marketing, and sales; develop and deploy machine learning models and AI technologies while managing large data sets.

The Security Managed Services Engineer (L2) ensures operational security infrastructure through monitoring and resolving incidents, collaborating on projects, and maintaining SLA compliance.

The Technical Content Writer will create engaging and accurate content on data analytics, collaborate with experts, and optimize for SEO to drive traffic.

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

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 Senior Software Engineer will design and maintain backend software, APIs, and collaborate with various teams to enhance product offerings and scale services.

Lead and scale QuillBot's AI Engineering & MLOps function by overseeing the full ML lifecycle, optimizing performance, and mentoring a team while collaborating cross-functionally.

Lead the AI product strategy at Goodnotes, overseeing development across various AI initiatives and ensuring alignment with company vision.

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.

The Data Scientist will analyze structured and unstructured data, build predictive models, and explore generative AI applications to support decision-making and product enhancement.

Lead AI initiatives, craft product vision, manage lifecycle, utilize data for decisions, and foster collaboration across teams.