Top Natural Language Processing Jobs in Boston, MA

Leads Pfizer’s global procurement organization across R&D and supply operations, including direct and indirect materials, laboratory services, manufacturing, logistics, facilities, capital, MRO, and research services. Owns category strategy, strategic sourcing, negotiations, supplier performance, supply risk, resilience, ESG, and third-party risk management. Partners with senior stakeholders, leads multiple category teams, develops procurement talent, and uses analytics and AI to improve value, decision-making, and supply assurance.

Prospect and qualify property management clients through cold calls, emails, social outreach, and multi-channel campaigns. Generate qualified leads and sales pipeline for Account Executives, communicate with client executives, manage new business opportunities, and consistently meet or exceed quotas. The role requires CRM proficiency, high-touch outbound sales experience, adaptability, urgency, and five days per week in the office.

Develop, fine-tune, train, and optimize computer vision and machine learning algorithms. Manage experiments, data, testing, validation, and reproducibility using MLOps tools. Research emerging ML techniques, analyze field-test data, and transition algorithms into production across cloud, on-premises, and embedded environments. Collaborate with engineers and national security customers to deliver mission-critical AI and natural language processing capabilities.

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 the technical direction for Deepgram’s Console team, architecting developer-facing products including Console, Playground, account management, billing, analytics, and AI tooling. Build full-stack features, guide large cross-functional projects, drive self-serve growth infrastructure, mentor engineers, establish technical standards, and partner with senior leaders on strategy, prioritization, and product-led growth.

Supports enterprise and mid-market sales by creating customized demonstrations, presenting SaaS solutions, managing pilot implementations, resolving customer issues, and identifying expansion opportunities. Builds customer relationships, provides support, gathers product feedback, and improves internal tools and processes. Requires technical sales experience, website technologies, CMS platforms, databases, REST APIs, and solution-selling expertise.

Partner with enterprise financial firms to design and implement scalable practice management programs. Lead executive engagement, success roadmapping, content and curriculum development, and live facilitation. Drive adoption through program design, data-driven recommendations, and feedback to Product. Travel regularly to client sites and industry events to deliver sessions and represent Zocks as a subject-matter expert.

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.

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.