Top Natural Language Processing Jobs in Boston, MA

Leads learning measurement and impact strategy across Pfizer’s commercial learning portfolio. Defines evaluation standards, metrics, and success measures; oversees behavior- and business-level studies; validates relationships between learning, competency, and business outcomes; presents evidence and recommendations to senior leaders; and builds the organization’s measurement practice and analytical capabilities.

Develop and evaluate advanced machine learning methods for biomedical, clinical, molecular, and scientific data. Build foundation models, multimodal and graph-based systems, generative methods, and agentic reasoning tools. Design rigorous experiments, benchmarks, and validation frameworks; assess robustness, uncertainty, interpretability, and scientific utility. Collaborate with researchers, engineers, computational biologists, and domain experts to translate research into reusable capabilities supporting drug discovery and development.

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.

Own lifecycle email and in-app campaigns for portfolio products using Iterable and HubSpot. Build, schedule, test, and optimize customer journeys; coordinate cross-functional marketing projects; develop A/B tests; analyze campaign performance; improve execution systems and processes; and support cross-product adoption across Superhuman’s product suite.

Own complex technical support issues from reproduction through resolution, troubleshooting APIs, webhooks, workflows, integrations, and AI agent behavior. Escalate well-documented issues to Engineering, identify recurring patterns, and partner on product improvements. Create runbooks and troubleshooting guides, coach Tier 1/2 and BPO teams, support critical incidents and premier accounts, participate in on-call rotation, and handle sensitive customer data appropriately.

Build and operate Deepgram’s deal desk, including approval matrices, pricing playbooks, credit and promotion guidelines, non-standard deal reviews, pricing analysis, Salesforce CPQ workflows, and audit-ready approvals. Partner with Sales, Customer Success, Product, and Finance on pricing, packaging, renewals, and revenue recognition. Use AI for first-pass deal reviews and continuously improve desk rules and processes.

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.