Top Senior Machine Learning Jobs in Boston, MA

Develop and productionize a next-gen Dispatch System, build ML models, automate processes, and collaborate with various teams while mentoring other engineers.

Seeking a machine learning engineer to build solutions for personalization, automated experimentation, predictive modeling, and content generation, impacting customer interactions.

Lead the Notifications Relevance team, developing machine learning models for personalization and user engagement, while managing engineering efforts and team growth.

Design and deploy machine learning algorithms, develop production systems, and collaborate with stakeholders to align ML solutions with business objectives.

Design, develop, and maintain algorithms for engineering applications, manage datasets, and implement machine learning workflows in an AI Copilot startup.

Lead the design, development, and implementation of machine learning applications, focusing on architecture, model training, and deployment using emerging technologies.

The Senior Machine Learning Engineer will develop advanced ML models, create LLM-based solutions, and collaborate cross-functionally within an agile team to enhance customer experience.

The Senior Staff Machine Learning Engineer will lead system development for personalization and ranking, mentor engineers, and influence technical direction within large-scale systems.

As a Lead Software Engineer, you will focus on R&D of machine learning technologies, developing tools for circuit characterization, and improving simulation capabilities.

Lead machine learning projects from conception to production, enhance ranking systems, mentor team members, and implement high-performance distributed systems.

The Senior Machine Learning Engineer will develop, deploy, and optimize machine learning applications, collaborating with cross-functional teams to enhance AI services.

The Staff Machine Learning Engineer will apply advanced ML techniques to enhance automation and productivity at Coinbase, mentoring junior engineers and managing projects.

Design and implement scalable machine learning pipelines, mentor junior team members, ensure deployment standards, build CI/CD pipelines, and establish best practices for ML systems.

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.

Design, build, and optimize ML systems for recommendations at scale. Collaborate with teams on data pipelines, model development, and experimentation.

The role involves designing, building, and optimizing large-scale ML systems for personalized recommendations, focusing on data ingestion, model training, and collaboration with cross-functional teams.

Lead a team of data scientists to develop and integrate advanced machine learning models for clinical trial execution, improving trial efficiency and patient recruitment.

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 enhancing developer tools for GM's AV engineers, addressing pain points, and mentoring team members to improve productivity and maintain quality code efficiency.

Lead research and development of advanced machine learning solutions, optimizing large-scale infrastructure and providing technical guidance on high-impact projects.

As a Senior to Principal Machine Learning Engineer, you'll lead the architecture and development of the Agentic AI platform, focusing on LLMs. Responsibilities include enhancing LLM performance, designing evaluation methodologies, and establishing safety protocols for LLM use.

Lead a team of ML engineers in developing advanced personalization systems. Balance technical leadership with hands-on model development, focusing on system architecture and improvements.

Lead the development and implementation of AI, machine learning, and data science solutions for a digital health platform, focusing on chronic condition management. Responsibilities include overseeing federated data systems, predictive modeling, and cross-functional collaboration.