Top Machine Learning Jobs in Hyderabad

Own and evolve one or more B2B SaaS product lines: define roadmaps, write specs and user stories, build wireframes/prototypes, integrate GenAI/ML features, collaborate cross-functionally, use analytics to drive decisions, and deliver high-quality releases on schedule.

The Hyperscalers and Commercial Lead will develop technology-driven business strategies, drive customer adoption, and manage end-to-end sales processes while working closely with cross-functional teams.

The Customer Success Business Partner at Lyric drives customer adoption and retention for strategic accounts, leveraging expertise in AI and supply chain operations.

Design and productionize ML models for search relevance and personalization. Collaborate on ML services with backend teams under performance constraints.

The role requires a skilled Machine Learning Engineer to create complex models and AI solutions while collaborating with teams to enhance products and services.

As a Demo Engineer, you support pre-sales by designing AI-driven demos and proof of concepts, collaborating closely with teams to showcase Cresta's capabilities.

As a Machine Learning Engineer, you will solve business problems using machine learning and AI, develop POCs, and support team growth through collaboration and knowledge sharing.

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.

The Post Doctoral Scientist will analyze large-scale datasets related to cardiometabolic diseases, using statistical and computational techniques to identify genetic factors and support therapeutic development.

The Senior AI/ML Engineer will lead the development of enterprise AI solutions, owning architecture and delivery, mentoring engineers, and ensuring compliance with responsible AI practices.

Seeking a senior AI/ML engineer with 6+ years experience to design and scale AI/ML platforms, innovate, mentor, and solve complex data challenges.

The role involves delivering AI solutions, developing models, supporting Agile practices, collaborating with teams, and focusing on execution and delivery.

The role involves owning the MLOps infrastructure, migrating detection pipelines, building CI/CD pipelines, and ensuring system reliability in production.

The role involves designing and optimizing large-scale ML data pipelines, ensuring high-throughput data ingestion and processing, collaborating with teams on data workflows, and architecting GPU-based environments.

The role involves building and automating ML models and data pipelines, analyzing data, and presenting insights based on user behavior and input data.

As a Senior Data Engineer, you'll design, develop, and maintain cloud data solutions, build data pipelines, ensure data quality, and collaborate with clients and teams.

This role involves developing real-world applications using modern AI models and LLM frameworks, focusing on deployment and implementation of AI features.

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

Develop and optimize machine learning models, manage project priorities, and improve real-world solutions using advanced ML techniques.

Design, develop, and deploy machine learning models and AI solutions. Collaborate with teams for intelligent automation and conduct research on new AI technologies.

Develop and scale data management systems for AutoML and forecasting platforms, ensuring data reliability and implementing SLAs across pipelines.