Top Hybrid Machine Learning Engineer Jobs in Boston, MA

The Staff Machine Learning Engineer will design and build scalable ML systems for health insights, collaborating with cross-functional teams to ensure compliance and quality in production-ready services.

As a Sr. Distinguished Engineer at Capital One, you will lead AI/ML engineering teams, design and build ML applications, mentor engineers, and drive technology innovations in machine learning.

The ERP AI Engineer - Manager at PwC leads teams in AI/ML engineering, manages client relationships, and designs AI solutions, all while mentoring team members and addressing complex business challenges.

Design, implement, test, deploy, and iterate machine learning and optimization models and systems. Collaborate with data scientists, engineers, and product managers to scale ML solutions, research new techniques, and improve data quality and predictive applications.

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.

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.

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

Lead large, cross-functional technical programs for autonomy, owning model development and release cycles. Act as DRI for behavioral capabilities, integrate Prediction and ML Planning, dig into ML/behavior issues, identify and mitigate technical risks, and align roadmaps with engineering, product, and executive stakeholders to deliver driverless milestones.

Lead design, training, and deployment of large-scale ML models (LLMs, diffusion, GNNs). Own end-to-end training pipelines, distributed training, evaluation, and inference architecture. Collaborate with data and infra teams, drive reproducible model development, and provide technical leadership and mentorship from research through production.

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