Top Machine Learning Jobs

The role involves designing, building, and scaling machine learning platforms to enhance user experiences through personalized content recommendations. Responsibilities include maintaining platform services and conducting online AB tests for optimization.

The Applied Machine Learning Research Scientist will translate ML techniques into scalable systems, improve LLM performance, and optimize workflows while collaborating closely with researchers and engineers.

Support development of AI-powered solutions by assisting in machine learning model creation, data analysis, and collaboration with engineering teams.

The ML Engineer will design, develop, and implement machine learning models, manage ML pipelines, integrate APIs, and collaborate with teams to deploy solutions.

Lead research and development of advanced fraud detection ML models, experiment design, productionizing prototypes, and mentoring engineers.

As a Machine Learning Engineer, you will develop and deploy innovative ML models addressing challenges in the electric grid, collaborating with a diverse team on multimodal ML applications.

The role involves developing machine learning algorithms, optimizing LLM deployments, and managing deployment pipelines while mentoring team members.

As a Senior Machine Learning Engineer, you will develop scalable infrastructure for distributed LLMs, optimize performance, and lead innovation in AI deployment while collaborating with cross-functional teams.

Lead the implementation of machine learning models, mentor junior staff, and ensure data integrity while collaborating with stakeholders.

As a Staff Machine Learning Software Engineer, you will bridge internal product teams and customer deployments, contributing to core products, defining engineering tasks, and working on data science and ML model training.

Develop, validate, and deploy machine learning models and scalable ML pipelines. Preprocess and analyze data, run experiments, collaborate with senior engineers and stakeholders, and support model risk governance and regulatory-compliant AI applications (fraud detection, credit scoring, marketing analytics).

Design, build, and scale AI/ML solutions for research and insights products. Lead experiments and manage model deployment in production environments.

The Senior ML/AI Engineer designs and implements ML/AI solutions, leading end-to-end ML/AI pipelines, collaborating with teams, mentoring, and developing infrastructure for large-scale data-driven products.

As a Machine Learning Intern, you will develop and implement ML algorithms, collaborate with engineers, and participate in hackathons to enhance the user experience at Tinder.

Lead the development of machine learning models for advanced AI-native manufacturing systems. Focus on integrating physical data with physics-based simulations for control and autonomy in metal additive manufacturing.

The Staff Engineer in AI & ML will lead the design, development, and implementation of analytics and machine learning solutions for manufacturing operations, enhancing data-driven performance management and decision-making.

As a Senior Machine Learning Engineer, you will own the ML stack, develop generation systems, improve quality, collaborate cross-functionally, and build data pipelines.

The AI/ML Engineer will develop and integrate AI/ML solutions for autonomous warfare, ensuring compliance with cybersecurity policies and collaborating on large language model projects.

The Principal Applied ML Researcher leads the ML strategy for a platform, focusing on applied ML systems and agent workflows to ensure reliable execution in regulated environments. They drive innovations, oversee the development lifecycle, and lead the integration of LLMs into production systems while ensuring compliance and performance metrics are met.

As a Software Engineer in Machine Learning, you will develop and deploy production-grade ML solutions, collaborate with teams, and establish operational excellence in ML practices.

The Applied ML Engineer will productionize and scale machine learning systems for a voice AI platform, optimizing deployment and performance in healthcare environments.

The Machine Learning Engineer will help build a platform for interpretable AI systems in life sciences, leading research, implementing projects, and ensuring system performance.

Design, develop, and implement machine learning models and algorithms to solve complex problems, collaborating with data scientists and software engineers.

Design and implement 3D machine learning models, process reality capture data, and integrate AI solutions in production environments for robotics applications.

As a Machine Learning Engineer, you will leverage LLMs to improve language understanding, design ML models, and collaborate on innovative features.