Top Senior Level Machine Learning Jobs in Seattle, WA

As a Senior AI Engineer at Cisco ThousandEyes, you will be responsible for the design, implementation, and maintenance of large-scale AI/ML pipelines. Your role includes training and tuning models, performing evaluations of deep learning and transformer models, and building evaluation frameworks and metrics.

The Sr Machine Learning Engineer will be responsible for developing and maintaining machine learning algorithms for Hulu's recommendation system. This includes feature engineering, optimizing algorithms, collaborating with product teams, and maintaining real-time data pipelines.

The Staff Machine Learning Engineer will develop and productionize machine learning models, collaborate with product teams, ensure code quality, research emerging technologies, and share knowledge through presentations. They will focus on solving business challenges with AI-driven solutions and implementing machine learning systems.

Develop and optimize Large Language Model solutions for customers, build ML pipelines, provide technical mentorship, and collaborate across teams to influence product strategy.

The Principal Machine Learning Engineer at Unity will lead the development and optimization of machine learning applications for the Ads Applied Research team, overseeing advanced ML models and contributing to product innovations. The role requires collaboration with product and engineering teams to address data and ML capabilities and align with strategic goals.

As a Senior Data Scientist specializing in Machine Learning at Lyft, you will develop algorithms and mathematical models to optimize rideshare supply and demand, driving decisions with data. You will collaborate with cross-functional teams, conduct exploratory data analysis, and implement algorithms in production, playing a key role in enhancing product offerings and user experiences.

As a Senior Data Scientist at Twitch, you will enhance machine learning systems and analytics for product strategies. You will drive improvements in recommendation and search algorithms, define core metrics, design experiments, and collaborate across teams to inform business decisions.