Top Natural Language Processing Jobs in Boston, MA

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.

Designs, builds, and operates production-grade agentic AI systems and orchestration frameworks. Responsibilities include prompt architecture, tool and API integrations, monitoring, evaluation, cost controls, reliability improvements, and governance documentation. The engineer collaborates with data science, data engineering, and governance teams to ensure reliable, compliant workflows using structured healthcare and pharmaceutical data.

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.

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.

Manage full-cycle talent acquisition, including candidate screening, assessment calls, communication, sourcing, pipeline development, recruiting platform management, and applicant tracking data. Partner with hiring managers to meet hiring goals while delivering an excellent candidate experience and strengthening the employer brand. The role requires proactive outreach, strong organization, relationship-building, adaptability, and effective remote collaboration.

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.

Develops and commercializes partner-built solutions across the Superhuman Suite. Responsibilities include shaping joint value propositions, creating pitch and demo assets, enabling alliance managers and partners, packaging repeatable solutions, coordinating launches, supporting partner growth, and tracking post-launch performance. The role works across Alliance Programs, Partner Marketing, Technical Alliances, Product, and solution architecture, with approximately 25% international travel.

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.