Top AI & Machine Learning Jobs in Boston, MA

Leads advanced analytics, machine learning, and AI initiatives for Finance, developing predictive models, forecasting solutions, optimization, automation, anomaly detection, and conversational analytics. Partners with Finance, Data, Technology, and Engineering teams to translate business challenges into scalable solutions, establish governance and testing frameworks, evaluate model performance and bias, and drive adoption. Provides technical leadership and mentorship while supporting Finance transformation and continuous improvement.

Owns the vision, roadmap, governance, and lifecycle management of AI/ML platform capabilities. Translates stakeholder needs into platform requirements, prioritizes integrations and improvements, partners with engineering teams, drives adoption, and monitors reliability, performance, security, cost, and technical debt. The role also supports agile delivery, communicates releases and incidents, reports progress to leadership, and assists with critical IT escalations.

Develops and oversees enterprise AI governance policies, standards, controls, monitoring, and risk-management processes. Advises business and technology leaders on responsible AI, regulatory requirements, controls, and mitigation strategies. Coordinates with cybersecurity, privacy, legal, compliance, architecture, and engineering teams; evaluates control effectiveness; drives corrective actions; supports audits, executive reporting, and governance committees; and promotes adoption through stakeholder education. Requires 8+ years in data analysis, reporting, or related fields, with SQL, analytics, data modeling, and visualization experience.

Develops, tests, evaluates, and deploys machine learning models using established architectures and frameworks. Supports feature engineering, data preprocessing, automated training and monitoring pipelines, and production AI integration. Collaborates with engineering and product teams on AI requirements, researches methods to improve model performance, and supports urgent IT incidents. The role requires strong Python and machine learning experience, knowledge of deep learning and generative AI, and advanced quantitative education.

Leads enterprise data science and AI solution delivery, including ML, generative AI, and predictive model development, deployment, monitoring, governance, and integration into business workflows. Drives AI adoption, change management, value realization, and evaluation of emerging technologies while partnering with data, engineering, and platform teams. Builds and leads AI delivery teams and ensures compliance with security and governance standards.

Develop, test, deploy, and serve machine learning models and agentic AI capabilities. Build feature engineering, experimentation, training, monitoring, and REST-based model-serving workflows. Collaborate with data science, engineering, product, and MLOps teams to productionize AI solutions at enterprise scale using distributed computing, Databricks, cloud platforms, and containerized infrastructure. Support model performance improvements, generative AI initiatives, and urgent IT escalations.

Develop advanced personalization and recommendation systems for digital grocery shopping. Build, deploy, monitor, and maintain machine learning pipelines and microservice APIs supporting production inference. Apply natural language processing, generative AI, large language models, agentic AI, recommendation models, deep learning, transformers, and classical machine learning techniques to real-world business problems. Evaluate and tune models, communicate technical results, and contribute to scalable AI solutions.