Top Machine Learning Jobs in Bengaluru, KA

Seeking an AI Engineer to develop Generative AI models for healthcare and financial services industries, with a focus on senior care. Responsibilities include designing AI models, managing MLOps pipelines, mentoring team members, and refining machine learning models.

Develop, fine-tune, and deploy generative AI models to create innovative solutions. Collaborate with teams to integrate AI models, analyze data, experiment with techniques, and assist in AI application development. Document work for reproducibility.

Lead the design, development, and deployment of advanced machine learning models and algorithms for various applications. Collaborate with cross-functional teams to translate business requirements into technical solutions. Mentor junior developers and stay updated with AI/ML advancements.

Design machine learning models to enhance system observability, proactive monitoring, and root cause analysis. Collaborate with multiple teams to integrate AI/ML capabilities into tooling, monitoring platforms, and processes to build a smarter infrastructure.

The Staff AI Scientist at GE HealthCare will work on developing and implementing novel machine learning algorithms in the area of LLM for automation of clinical tasks. Responsibilities include building prototypes, exploring human feedback, and staying current with AI technologies. Candidates must have a Master's Degree in a STEM field with 5 years of AI development experience or a Ph.D. with 3 years of AI development experience. Strong expertise in generative AI models and implementation experience in Python and C++ are required.

Lead NLP Engineer responsible for developing efficient self-learning NLP search algorithms and systems. Requires expertise in NLP techniques, machine learning methods, and text representation techniques. Must have a strong background in statistics, classification algorithms, and software architecture.

Develop cutting-edge techniques in deep learning, machine learning, and data analytics. Collaborate with key customers and internal teams to optimize GPU performance. Requires Masters degree or PhD in engineering or computer science.