Top Hybrid Machine Learning Jobs

In this role, you will build and evolve an AI platform by developing next-generation Large Language Models for enterprise applications. Responsibilities include applying ML methods to real-world problems, conducting LLM benchmarking, data collection, collaborating with cross-functional teams, and contributing to innovative developments and research publications.

As a Senior Machine Learning Engineer, you will develop and optimize recommendation algorithms for Disney's streaming platforms, collaborate with cross-functional teams, maintain existing algorithms, and improve personalization strategies to enhance user experiences.

As a Senior Data Scientist in GM Motorsports, you will collaborate with cross-functional teams to develop analytics and predictive models using advanced machine learning and AI techniques. Your responsibilities include data preprocessing, model building, and presenting findings through data visualization, all aimed at enhancing race team performance and achieving competitive advantages.

The Senior Software Engineer in Machine Learning is responsible for architecting and scaling personalization and search platforms for the Max streaming app. The role involves collaborating with data scientists, contributing to machine learning systems, optimizing code, and advocating for customer-focused innovation.

As a Data and Analytics Staff Consultant, you will collaborate on consulting projects, author project documents, manage your time efficiently, and support clients with training and knowledge transfer. You will also assist in project scope prioritization and adherence to delivery models while refining business and technical requirements.

As an Applied AI Scientist at ZS, you will develop advanced algorithms, execute statistical techniques on large datasets, evaluate emerging technologies, and contribute to the firm's thought leadership by researching and publishing on evolving topics.

As a Staff Machine Learning Engineer on the Risk team, you will develop machine learning solutions to mitigate risk and fraud while collaborating with various stakeholders to balance business loss and customer experience. You will leverage extensive transaction data to understand customer behavior and create innovative products.