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 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.

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 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.

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.