Top Hybrid Machine Learning Engineer Jobs in Boston, MA

Lead design, build, deploy, and maintain production ML and AI systems (including LLM inference, RAG, similarity search, observability, and governance). Collaborate cross-functionally to create data pipelines, retrain and monitor models, and apply responsible, explainable AI practices while contributing technical vision and roadmap for AI solutions.

Individual contributor on an applied science team building production ML and software systems for media accessibility. Responsibilities include prototyping, evaluation, productionization, experiment design and analysis, code and design reviews, and reporting results for audio/video/NLP/generative AI projects.

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.

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 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.

As a Senior Machine Learning Engineer, you'll build and deploy AI/ML models, design workflows, and drive product development in a startup focused on the collectibles industry.

Design, build, and monitor statistical and machine learning models (including generative AI and RAG) to analyze large datasets, detect anomalies, forecast trends, and support business stakeholders. Lead projects, develop automated monitoring, improve data collection, evaluate analytical tools, and produce visualizations using Qliksense/Tableau/PowerBI to communicate insights to technical and non-technical audiences.