Top Remote Senior Level Machine Learning Engineer Jobs in Boston, MA

The role involves designing and building machine learning systems for personalized user experiences by leveraging cultural understanding using LLMs. You'll manage data pipelines and collaborate across teams to integrate foundational AI tech.

As a Machine Learning Scientist at Nucs AI, you will develop innovative ML methods for medical image analysis, collaborate with clinicians, and contribute to clinical validation studies, impacting cancer diagnostics.

Design and develop geometry processing algorithms and simulation services for engineering applications, focusing on integrating machine learning with practical engineering tasks.

Define ML strategy and build production ML systems end-to-end (data pipelines, training, evaluation, inference). Own data strategy, integrate ML with product/backend, write production-quality code, and recruit and mentor the ML team while setting technical direction.

The Staff AI Engineer will design, implement, and maintain machine learning algorithms and systems, integrating AI components into applications and collaborating with cross-functional teams using cloud technologies and DevOps principles.

The Staff Machine Learning Engineer will lead ML initiatives, develop AI systems, optimize pipelines, and mentor team members to automate healthcare processes.

As an ML/AI Engineer, you'll build and operate the LLM platform, integrating models, optimizing performance, and collaborating cross-functionally to ensure reliable AI systems.

Design, iterate, and productionize ML models for recommendation, ranking, routing, and monetization. Lead A/B testing and causal measurement, build dashboards and analytics, define metrics, collaborate with Product and Engineering, and scale ML/analytics infrastructure and model lifecycle management.

The Senior Consultant in AI will design, build, and deliver AI/ML solutions on Azure, engage with clients, and develop project components independently.

The Machine Learning Engineer will execute the full ML lifecycle, collaborating on model implementation and improving customer experiences through data-driven insights.