Top Machine Learning Jobs in Boston, MA

As a Machine Learning Engineer, you'll design and ship LLM-based solutions, collaborate across teams, and improve storytelling capabilities at scale.

As a Machine Learning Engineer Intern, you'll enhance model performance, develop production-grade tools, and automate workflows while receiving mentorship from experienced ML professionals.

Develop and optimize machine learning models for data extraction from tax documents, collaborate on software integration, and mentor junior team members.

The role involves architecting scalable ML solutions, collaborating on data processing, mentoring junior engineers, and promoting best practices in machine learning.

As a Senior Staff Machine Learning Engineer at Affirm, you will lead complex ML system design and implementation, mentor engineers, and drive innovative ML strategies for financial services.

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

Lead the Applied ML team's experimentation efforts, mentoring scientists and engineers to improve AI-driven methodologies and collaboration across various product areas.

Design and implement machine learning pipelines for fraud and payment systems, collaborating with data scientists and engineers to enhance reliability and decision-making.

As a Staff Machine Learning Engineer, you will optimize Quora's ad products by applying machine learning algorithms, taking ownership of systems, and collaborating across teams.

As Director of AI/ML, lead the ML organization, set technical vision, mentor a high-performing team, and contribute to model development and production deployment.

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

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

The Senior Applied Scientist II is responsible for designing and implementing ML models to optimize the supply chain, collaborating across teams, and driving data-driven decision-making.

As a Senior Machine Learning Engineer, you will develop scalable ML solutions, collaborate with teams, optimize models, and implement best practices for deployments and infrastructures.

The Senior Machine Learning Engineer will develop ML APIs, build data pipelines, and collaborate across teams to enhance ML models and applications.

As a Senior Machine Learning Engineer, you will design ML infrastructure, lead zero-to-one initiatives, collaborate on projects, and enhance scalability in the development of ML applications.

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

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

Develop machine learning models to differentiate normal and attack behaviors, collaborate with security researchers, and analyze algorithm performance.

As a Machine Learning Engineer, you will develop and operationalize models for content understanding and discovery, collaborating with cross-functional teams and stakeholders to solve impactful problems using machine learning.

Lead data-driven decisions in weather and climate analytics by developing machine learning models, managing projects, and mentoring team members.

Develop electrical system ontology for data centers, deploy advanced anomaly detection using machine learning, monitor telemetry, and collaborate with teams to enhance reliability.

As a Principal AI/ML Software Engineer, you'll lead ML technology strategy, develop innovative solutions, and influence technical decisions across the organization while guiding high-performing teams.

The engineer will train, evaluate, and deploy ML models for understanding driving environments, focusing on motion prediction and planning for autonomous vehicles.

Responsible for training and deploying ML models for scene understanding, behavior prediction, and planning in autonomous vehicles. Collaborate on designing and analyzing experiments, maintaining evaluation code, and improving model performance.