Top Senior Level Machine Learning Jobs

As a Machine Learning Engineer on the On-Device ML team, you will design and prototype new features, build and implement ML models, collaborate with product teams, and launch and monitor model deployments, all aimed at enhancing Grammarly's writing assistance capabilities on devices.

The Director of Data Science and Machine Learning will lead the Machine Learning, Data Science, and Product Analytics teams, drive data-powered insights for product performance, and collaborate across departments to optimize business growth. Responsibilities include team leadership, defining strategic vision, fostering collaboration, and overseeing the development of ML and DS models.

The Senior Staff Scientist will lead the development of hybrid AI applications optimized for various platforms, collaborate with teams to integrate quantum algorithms, and foster client relationships while representing the company at conferences. The role also includes discovering new algorithms and developing core intellectual property in quantum computing.

The Senior Machine Learning Engineer will develop and optimize NLP algorithms, train large language models, collaborate with cross-functional teams, and mentor junior engineers, all while advancing the company's technology stack and delivering new features rapidly.

The Senior Consultant/Engineer will deliver complex solutions in areas like analytics and data strategy, manage client engagements, and oversee project budgets. The role requires strong technical skills in SQL and data modeling, along with business acumen in managing client expectations and relationships.

The Director of Machine Learning Operations will lead the ML Ops team to develop, implement, and oversee machine learning strategies. Responsibilities include managing ML infrastructure, deploying models, ensuring performance and scalability, and collaborating with cross-functional teams to integrate ML solutions into the advertising technology platform.

As a Senior Distributed Systems Engineer (Machine Learning), you will develop and maintain high-quality, scalable AI solutions and services for a Machine Learning Platform. You will collaborate with product and engineering stakeholders to understand requirements, minimize deployment risks, and integrate AI innovations into product development, ensuring the delivery of tangible business value.