Top Machine Learning Jobs

Design and develop scalable ML systems for healthcare, collaborating with teams to enhance products and maintain efficient infrastructures.

The Senior Engineer will innovate and develop AI/ML solutions using Java to enhance customer experiences and exceed expectations.

The Senior Machine Learning Engineer will design and implement high-performance CTR and CVR prediction models, refine systems for user behavior modeling, and ensure model reliability through performance monitoring while engaging with stakeholders.

Design and implement high-performance CTR and CVR prediction models for ad ranking systems. Collaborate on system quality and direct future team strategies.

As a Senior Staff ML Engineer, you will architect ML systems, lead technical direction, and build recommendation platforms to enhance user interactions at Grindr.

Design and implement high-performance CTR and CVR prediction models, ensuring reliability and quality while collaborating with team leads on project direction.

Develop, implement, and maintain CTR and CVR prediction models for ad systems; collaborate with teams to enhance performance and communicate concepts clearly.

The Staff Machine Learning Engineer will develop advanced Document AI models, solve complex modeling challenges, lead LLM fine-tuning, and provide leadership in a collaborative environment.

The Senior Machine Learning Platform Engineer will develop and expand Strava's machine learning platform, ensuring model performance, reliability, and stability in a collaborative environment.

Intern will assist in developing machine learning models, improving product performance, and performing data analysis. Responsibilities include coding algorithms, testing, and documentation.

The Machine Learning Engineer develops ML models, performs feature engineering, conducts model evaluation and optimization, and collaborates with teams.

As a Machine Learning Intern, you'll assist in developing and implementing machine learning algorithms, working with data preprocessing and model validation, while collaborating with cross-functional teams.

Lead AI and machine learning projects, create workflows and models, analyze data from diverse sources, and present insights to non-technical audiences.

The AI & Machine Learning Director will lead machine learning projects, design data workflows, and utilize advanced data analysis and visualization to drive business insights.

As a Software Engineer specializing in Machine Learning, you'll enhance video solutions, develop APIs, mentor engineers, and ensure high-quality code in a collaborative team.

The ML Engineering Intern will contribute to the Nebula LLM development, tackle machine learning challenges, and gain hands-on experience in AI and language technology.

The role involves developing AI/ML models to predict organoid growth and optimizing differentiation protocols through computational methods, collaborating with experimental teams.

The Staff Machine Learning R&D Engineer will innovate machine learning algorithms for spatial computing, collaborate with teams, and translate research into production solutions.

The role involves advancing ML systems, building APIs, mentoring engineers, and ensuring high code quality and engineering practices.

Develop custom models and algorithms for large datasets, collaborate with stakeholders to leverage data for business decisions, and assess data sources and techniques.

Lead initiatives in model-based autonomous driving, developing end-to-end driving models and collaborating with cross-functional teams. Mentor senior engineers and influence technical direction.

The Machine Learning Research Engineer at Optiver will conduct research and develop deep learning models to improve trading strategies, while building robust pipelines and collaborating with other engineers.

As a Staff Machine Learning Engineer, you will enhance Coupang's search and discovery algorithms using ML, DL, and NLP to improve product relevance and user interaction.

Lead the development and strategy for machine learning algorithms in search and recommendation systems, focusing on personalization and deployment efficiency.

Lead the design and development of advanced recommendation systems and machine learning pipelines, optimizing performance for millions of users.