Top Natural Language Processing Jobs in Boston, MA

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.

Leads the architecture, development, and evolution of Pfizer’s global Medical Insights platform. Translates regional and business needs into scalable technical requirements, sequences roadmap work, coordinates infrastructure and technology partners, and evaluates new data sources, analytics methods, and AI approaches. Partners with stakeholders to deliver platform value, guide technical decisions, and support change management. Requires strong cross-functional influence, technical communication, and experience building data or analytics platforms in pharmaceutical, life sciences, or technology environments.

Owns the global operational backbone of the InsightXplorer medical insights platform, including access provisioning, licensing, user administration, request intake and triage, hosting coordination, governance, reporting, metrics, workload visibility, and resource oversight. The role manages competing priorities across regions, coordinates recurring team cadences, supports leadership-ready reporting, and oversees contracted resources while collaborating with technical partners and cross-functional stakeholders.

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.

Software engineering interns contribute to production features across Kensho teams, including machine-learning applications, APIs, services, platform abstractions, observability, deployment, and data ingestion systems. Interns participate in code reviews, production deployments, infrastructure as code, testing, documentation, and continuous learning while collaborating with experienced engineers. The role requires algorithm and data-structure knowledge, at least one technical area of expertise, adaptability, and practical projects or open-source experience.

Manage the full lifecycle of defense contracts, subcontracts, purchase orders, modifications, and agreements. Review and negotiate NDAs, teaming agreements, licenses, and contract terms; analyze FAR/DFARS requirements; monitor milestones, CDRLs, and deliveries; coordinate invoices and funding; track government-furnished property; maintain records; and support contract closeout while collaborating with government, prime contractor, technical, finance, and internal teams.

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.

Lead Deepgram’s corporate legal function, including governance, IPO readiness, financings, M&A, employee equity, international subsidiaries, and regulatory developments. Partner with Finance, People, and company leadership to build scalable legal processes for a fast-growing AI company. Establish an AI-native legal practice while advising on a broad range of startup legal matters.

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 partner-network relationships after agreement signing, managing onboarding, contractual commitments, co-marketing, advisor adoption, and network penetration. Drive net-new bookings, expansions, trials, conversions, webinars, demos, and enablement activities. Track activation and pipeline metrics in Salesforce, coordinate with strategic partnerships, marketing, sales, account management, RevOps, and product teams, and forecast bookings across multiple financial-advisor networks.

Develop product launch narratives and messaging that connect with customers and prospects. Create demos, case studies, webinars, campaigns, web content, and customer stories. Partner cross-functionally with product, sales, and customer success to ensure consistent positioning. Conduct customer and prospect research, identify market trends, and use data-driven insights to strengthen product marketing strategy.

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.

Lead an established RevOps and Enablement team to sharpen analytics, harden systems and data architecture, and scale AI-first workflows across Sales, Marketing, and CX. Own revenue tech stack, forecasting, GTM reporting, process optimization, and enablement programs while partnering with executive leadership to drive measurable revenue outcomes.