Top Hybrid Machine Learning Engineer Jobs in Boston, MA

Design, build, and deploy scalable AI and GenAI solutions by wrangling data, developing ML models, and maintaining data infrastructure. Collaborate with clients, perform complex analyses, apply NLP and deep learning techniques, and mentor junior team members to deliver production-ready AI systems.

Lead design and delivery of AI/GenAI solutions: build and deploy scalable ML models, manage data pipelines and infrastructure, mentor teams, ensure data quality and compliance, and collaborate with stakeholders to drive AI-driven business outcomes.

Develop and scale machine learning systems to enable AI coaching, collaborate across teams for member insights, and contribute to architectural decisions.

The Senior Machine Learning Engineer will design and deploy scalable machine learning models, optimize performance, and lead best practices while collaborating with cross-functional teams.

The Principal Data Scientist will design and develop machine learning systems, manage data pipelines, and collaborate with teams to improve products and services. This role requires significant experience in ML model deployment and communication with stakeholders.

As a Senior Lead Machine Learning Engineer, you'll design and implement machine learning applications, lead teams, and optimize systems and data pipelines while collaborating in an Agile environment.

The Machine Learning Scientist will develop AI frameworks for predictive modeling in oncology, collaborating with teams to enhance drug R&D efforts through advanced machine learning techniques and multimodal data integration.

As a Lead AI Engineer, you will design, develop, and scale backend and ML systems, mentor engineers, and collaborate to create predictive ML solutions.

As a Staff Machine Learning Engineer at Motional, you'll define ML systems' architecture, lead projects, mentor engineers, and drive technical strategy to optimize data discovery and model improvement for autonomous vehicles.

The Senior Machine Learning Engineer will develop and optimize ML infrastructure, create data pipelines, and model orchestration ensuring data quality and performance monitoring.

The ML Scientist will develop machine learning models for climate risk, collaborate across teams, and validate algorithms to improve predictions of weather extremes.