Top Natural Language Processing Jobs in Boston, MA

Leads measurement and product marketing for eight enterprise AI platforms. Builds shared KPI, taxonomy, scorecard, data-quality, and value-realization frameworks; translates usage and outcome data into executive insights and investment guidance. Oversees positioning, internal launches, campaigns, enablement, adoption, and audience segmentation. Partners across product, engineering, data, communications, and business teams while building and managing teams responsible for analytics, marketing, and communications.

Leads applied AI and machine learning strategy, development, evaluation, governance, and adoption across Pfizer’s Internal Medicine Research Unit. Translates foundation models, LLMs, agentic systems, and multimodal AI into reusable capabilities for scientific discovery, drug development, and evidence generation. Partners with scientists, digital teams, and external collaborators to identify high-value use cases, ensure methodological rigor, and guide responsible deployment. Requires strong technical leadership, scientific judgment, cross-functional influence, and experience applying AI in complex environments.

Leads product strategy, roadmap, lifecycle ownership, adoption, and measurable outcomes for a greenfield enterprise AI platform. Defines platform boundaries, governance controls, evaluation, registration, and cost-tracking capabilities while translating evolving risk, privacy, security, and GxP requirements into usable product features. Partners with engineering, design, legal, compliance, risk, security, and global agent-building teams to prioritize investments, guide delivery, communicate direction, and drive platform adoption.

Design, develop, prototype, integrate, and test electronic systems for innovative air vehicle and R&D platforms. Responsibilities include avionics, embedded systems, RF communications, power subsystems, analog and digital circuit design, PCB development, fabrication procedures, troubleshooting, and flight test support. The role requires cross-functional collaboration, hands-on system testing, and expertise in at least one area such as power systems, RF, or embedded control.

Build and evaluate machine learning models, agentic systems, LLM applications, and pipeline components under senior-engineer guidance. Interns will gain experience across the ML lifecycle, including problem framing, model selection, development, evaluation, and deployment support. The role involves collaborating with ML Engineers, Product Managers, Designers, and Full-Stack Engineers on scalable AI solutions.

Lead AML/BSA, KYC/KYB, fraud, transaction monitoring, and sanctions compliance programs. Manage banking and financial institution relationships, oversee investigations and UAR/SAR processes, translate regulations into operational controls, coordinate audits and examinations, track regulatory developments, and deliver compliance training. Partner cross-functionally with Legal, Product, Engineering, and Operations to support responsible product growth and regulatory readiness.

Leads SMB and commercial sales strategy, revenue performance, team development, pipeline forecasting, enablement, hiring, and complex enterprise deals. Partners with Product, Marketing, Customer Success, and executive leadership to scale go-to-market execution, improve sales consistency, and drive customer expansion across a multi-product SaaS environment.

Own end-to-end localization operations for enterprise clients, serving as the primary operational contact and trusted advisor. Coordinate stakeholders and cross-functional teams, manage localization workflows and configurations across TMS and project tools, resolve client and internal issues, and improve processes through documentation, automation, and AI-enabled solutions. The role requires localization or translation project management experience, client communication skills, familiarity with localization formats and CAT/TMS tools, and strong organizational abilities.

Leads Deepgram’s end-to-end Text-to-Speech research program, owning research strategy, technical direction, model development, evaluation, and production deployment. Advances neural audio modeling, prosody, expressiveness, multilingual generation, voice consistency, controllability, and inference performance. Builds and develops research teams, manages technical leaders, prioritizes experiments and compute, evaluates model quality, and partners with engineering and product leadership to ship production-grade models.

Own full-cycle recruiting across all company functions and experience levels. Responsibilities include posting jobs, screening applicants, building shortlists, coordinating interviews and debriefs, maintaining ATS data, partnering with hiring managers, improving recruiting processes, and delivering a strong candidate experience across multiple simultaneous searches.

The Sr. Machine Learning Engineer will develop and deploy ML solutions for healthcare, manage data pipelines, and work with large datasets to enhance healthcare delivery.

Leads and develops a team of 5–10 Customer Success Managers serving strategic cybersecurity accounts. The role drives adoption, consumption growth, retention, expansion, customer satisfaction, and executive-level engagement. Responsibilities include building scalable success processes and playbooks, managing escalations and forecasts, partnering with Sales, Product, Engineering, and Marketing, supporting hiring and coaching, and providing cybersecurity and AI expertise to customers and internal teams.