Top Senior Machine Learning Jobs in Boston, MA

Develop and optimize machine learning models and workflows to enhance insurance processes. Collaborate on model integration, monitoring, and improvement while driving innovation in modeling techniques.

Build and optimize machine learning models for 3D dental applications, research state-of-the-art methods, and implement MLOps best practices.

Lead the design, execution, and analysis of machine learning-driven product experiments to optimize ordering systems. Collaborate with stakeholders and mentor teams.

As a Senior Machine Learning Engineer, develop solutions for robotic perception, focusing on rare events in warehouses using cutting-edge AI and ML techniques.

The Senior Machine Learning Engineer will design multi-modal vision systems, optimize and deploy models, mentor junior engineers, and improve data strategies for robotic perception tasks.

Design and develop geometry processing algorithms and simulation models, manage datasets, and enhance machine learning workflows for engineering applications.

The Senior AI/ML Engineer will design and optimize ML models for production, lead deployment efforts, and manage model lifecycle, while mentoring junior engineers.

The Senior Machine Learning Platform Engineer will build foundational components for ML models, mentor junior engineers, and optimize streaming pipelines. Responsibilities include enhancing ML infrastructure and ensuring data quality.

Lead and mentor ML engineers and data scientists, overseeing ML strategy and development of scalable models for healthcare applications.

The Engineering Manager, Machine Learning will lead a team focusing on 3D deep learning and computer vision, manage the ML roadmap, and implement best practices for MLOps pipelines.

Leading the development of ML models for drug discovery, collaborating with multidisciplinary teams, and managing team members while ensuring data-driven decision-making.

The role involves leading research in probabilistic ML, collaborating with other experts, scaling experimentation, and deploying models. Candidates should have a strong research background and publications in top ML conferences.

The Senior Machine Learning Engineer will design and optimize ML discovery features, oversee projects, mentor engineers, and manage the ML lifecycle from data ingestion to model deployment.

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.

The Staff Machine Learning Engineer will define and build ML capabilities, design production systems, and lead ML strategy in a high-growth AI cybersecurity company.

The VP AI/Machine Learning will define and implement machine learning capabilities in a high-growth cybersecurity company, focusing on strategy, infrastructure, and building production systems. The role involves defining ML applications, data strategy, and mentoring an ML team.

Senior Software Engineer role focused on building AI capabilities for an engineering AGI product. Collaborate with a team to integrate cutting-edge machine learning into real-world engineering systems and shape product design.

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.

Lead and build the companys ML function: define strategy, design production ML systems and infrastructure, own data and evaluation practices, write production code, integrate ML into products, and recruit and mentor an expanding ML team.

The Machine Learning Engineer will work on unstructured data classification and clustering, utilizing their expertise in AI systems and various programming languages.

The Senior Machine Learning Engineer will utilize deep experience and insights to enhance communication and digital interactions through advanced machine learning tools and algorithms, focusing on unstructured data.

The Principal Machine Learning Engineer will develop optimization algorithms, enhance LLM deployments, and collaborate with research teams on model performance and compression.

Design, develop, and deploy scalable ML software systems for healthcare. Collaborate with teams to improve products and ensure performance and reliability.

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

The role involves designing and implementing scalable ML-based solutions, analyzing data patterns, and producing reports while staying updated on AI advancements.