Top Natural Language Processing Jobs in Boston, MA

Owns Pfizer GH&B’s AI-ready Snowflake data warehouse, data architecture, ontologies, governance, quality, lineage, access controls, and production reliability. The role supports AI/ML models, dashboards, and business-critical data applications; establishes testing, release, monitoring, and incident processes; directs contingent technical resources; and aligns business-specific data decisions with enterprise standards. Requires strong SQL, Python, Collibra, data warehousing, unstructured-data architecture, ontology, governance, and stakeholder-influence experience.

Build and improve ML platform tooling, infrastructure, workflows, and observability for machine learning models, LLMs, and agentic applications. Collaborate with ML and infrastructure teams, evaluate and integrate open-source tools, automate fine-tuning and evaluation pipelines, and debug distributed systems across infrastructure, networking, and application layers.

Lead technical vision and execution for autonomy and APNT solutions on unmanned aerial systems. Guide programs from research and development through flight testing and fielding, oversee multidisciplinary engineering teams, manage schedules and budgets, support systems integration, engage customers and partners, and identify new business opportunities. Provide technical oversight while driving successful delivery of mission-critical aerospace software and systems.

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.

Build and operate high-throughput backend services for AI agents, calendar, scheduling, integrations, real-time data pipelines, and APIs. Design platform infrastructure, event-driven systems, and client-server protocols using Go, PostgreSQL, Kubernetes, and cloud platforms. Collaborate with AI, product, and frontend teams, improve reliability through testing and infrastructure as code, and mentor junior engineers.

Owns Deepgram’s North American events and field marketing portfolio, including 20+ trade shows, conferences, partner programs, executive events, roadshows, and account-based initiatives. Responsibilities include event strategy, budgeting, vendor and contract management, partner funding, brand activations, sales enablement, pipeline attribution, lead routing, ROI analysis, and post-event reporting. The role partners closely with Sales, Demand Generation, Product Marketing, alliances, and Marketing Operations, while developing AI-powered workflows and supporting the Deepgram Speak event series.

Supports and maintains enterprise customer web integrations using Smartling’s web proxy solution. Owns technical tickets, troubleshoots browser and network issues, leads customer workshops, creates diagnostic scripts and tooling, manages production configuration changes, and collaborates with Engineering on product fixes. The role requires strong web technologies, debugging, communication, and customer-facing technical consulting skills.

Lead enterprise technical and business discovery, solution design, demonstrations, and proofs of concept for an AI platform serving financial institutions. Advise technical, security, compliance, and business stakeholders on AI architecture, integrations, and data handling. Develop reusable solution assets, identify recurring customer needs, support presales and post-sale delivery transitions, and provide feedback to Product and Product Marketing.

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.

Conduct threat hunting and technical research on nation-state and cybercriminal actors, malicious infrastructure, tools, and tactics. Produce finished intelligence, public research, and detection signatures; brief customers and represent the team publicly. Collaborate with geopolitical analysts, mentor teammates, improve intelligence processes, and use automation to increase efficiency. The role requires threat intelligence expertise, networking knowledge, analytical writing, customer communication skills, and familiarity with intelligence frameworks and research platforms.

Research and analyze cybercriminal activity across dark web and underground platforms, track threat actors and campaigns, produce intelligence reports, maintain covert sources and personas, investigate cryptocurrency and money laundering, and deliver actionable findings to customers. The role also uses OSINT, AI-assisted workflows, and intelligence platforms while contributing to automation and proactive threat research.