Top Natural Language Processing Jobs in Boston, MA

Design, implement, and scale end-to-end retrieval-augmented generation (RAG) pipelines. Build and optimize retrieval systems, embeddings, vector search, and LLM orchestration. Collaborate with product, design, and MLOps to productionize robust ML systems across large proprietary datasets.

Design, develop, and productionize agentic AI systems and retrieval methods for financial data. Work across the ML lifecycle—experimentation, deployment, monitoring—and collaborate with product, data, and MLOps teams to build scalable, evaluated agent and NLP solutions.

The Customer Training Specialist will ensure smooth client onboarding and transition, conduct trainings, gather feedback, and enhance user experiences with products.

Lead day-to-day accounting operations including payroll, AP/AR, fixed assets, reconciliations, and equity accounting. Prepare journal entries, month-end close, financial statements per U.S. GAAP, cash flow reports, budgets/forecasts, and audit support. Improve controls and processes while maintaining clear documentation and supporting stakeholders across the organization.

Lead enterprise commercial enablement for PC1: own proposal/SOW strategy, Salesforce and SFMC platform ownership, sprint-driven product delivery, AI enablement, digital budget management, and cross-functional digital project leadership to drive scalable commercial and marketing outcomes.

Build and operate high-throughput backend services powering AI agent orchestration, connector integrations, and real-time data pipelines. Design scalable core platform services, collaborate with ML, frontend, and product teams, implement infrastructure-as-code and CI/CD, and mentor junior engineers to deliver reliable, AI-powered features.

Lead demand generation programs for Superhuman Mail, collaborating with Sales and other teams to drive marketing-sourced pipeline growth through integrated campaigns, optimization, and performance analysis.

As a Data Scientist at Deepgram, you'll tackle complex audio data challenges, develop scalable data pipelines, and collaborate with teams to advance voice AI technologies.

Lead end-to-end delivery of complex technical programs spanning hardware, software, and research. Define workstreams, set milestones, coordinate cross-functional teams, identify and mitigate risks, dive into technical details, and build lightweight processes and tooling to scale AI/ML infrastructure and GPU/cloud deployments.

Own and build the full invoice-to-pay cycle, automate AP with AI, lead month-end AP close and subledger-to-GL tie-out, establish AP analytics, prepare AP for external audit, manage ERP migration and Ramp card program, and handle vendor/tax compliance and reporting.

Own and grow Smartling’s social presence across LinkedIn, Instagram, Facebook, X, YouTube and emerging platforms. Build channel-specific content calendars, run employee advocacy, adapt long-form assets into native social content, create and brief short-form media, track analytics and iterate, monitor brand mentions, and leverage AI tools to boost efficiency and outcomes.

Lead and scale the enterprise customer success function for Zocks, managing a team of Enterprise CSMs to drive adoption, value realization, renewals and expansion with large RIAs, broker-dealers, banks and financial firms. Build playbooks, metrics, and cross-functional partnerships while personally engaging executive stakeholders to ensure measurable customer outcomes.

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.

Drive marketing measurement, reporting, and data governance for demand generation and field marketing. Build dashboards, reconcile cross-system data, maintain attribution and pipeline measurement, automate integrations and workflows, and apply AI/LLM tooling to scale analytics and enable data-driven marketing decisions.

As a Principal Software Engineer, you will design and maintain scalable data pipelines, drive architectural improvements, and ensure reliability while collaborating across teams.