Top Senior Level Machine Learning Jobs

As a Staff Data Scientist at Coinbase, you will build advanced models, provide technical mentorship, and develop novel experimentation techniques to drive business value. Your role will involve creating sequential features based on user behavior and quantifying the impact of negative experiences on the platform.

Lead the design, development, and improvement of machine learning models for 3D computer vision in an innovative photogrammetry platform. Responsibilities include optimizing ML systems, deploying models, and staying updated on advancements in the field. This role requires hands-on leadership and a solid background in machine learning and computer vision.

As a Senior Machine Learning Engineer, you will design and develop machine learning applications, conduct experiments, work collaboratively with engineers, engage with clients, and mentor project teams, focusing on practical AI solutions for clients.

Looking for a Senior AI/ML Scientist with experience in creating, optimizing, and deploying ML and NLP solutions. Responsibilities include building and deploying AI solutions for document review, organization, and Q&A processes.

As a Senior ML/Research Scientist at NextSense, you will develop state-of-the-art wearable neurotechnologies, conduct innovative research, and apply machine learning and signal processing techniques to analyze biosignals and develop digital biomarkers for neurological conditions. You will collaborate with a team to translate research into practical applications and engage in writing scholarly publications.

The Principal ML Engineer will build and deploy scalable machine learning models, develop web applications for data insights, and collaborate with cross-functional teams to deliver impactful data-driven solutions. Responsibilities also include providing consulting services for data-driven decision-making.

The Staff Machine Learning Engineer will develop and fine-tune machine learning models, apply statistical techniques to analyze unstructured data, utilize pre-trained language models, optimize models for production, monitor performance, and work with teams to enhance product features and solutions.