Top Natural Language Processing Jobs in Boston, MA

Sales Development Representatives at EliseAI generate leads, communicate with clients, and manage a sales pipeline to support growth and account executives.

The Electrical Engineer will design and develop electronic systems, collaborate on integration tasks, and troubleshoot complex systems for air vehicle systems.

The Director Solution Engineering Lead will oversee engineering resources, drive AI solution innovations, and ensure alignment with business objectives and enterprise standards.

As a Full-Stack Software Engineer II, you will develop AI-centric web applications using TypeScript, collaborating on product and technical decisions while managing project priorities and deliverables.

The Senior ABX Manager will design and execute account-based marketing programs for strategic accounts, collaborating with sales to drive engagement and revenue.

Design and implement secure, scalable backend services for voice agents, integrate AI models and telephony, improve inference, debug concurrent systems, and collaborate with Product to deliver features end-to-end.

The Enterprise Account Executive will drive sales by managing the sales process, generating new business, engaging with prospects, and achieving revenue targets.

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.

Own and grow Hebbia's Middle East enterprise sales: prospect, run demos, negotiate and close large deals with sovereign wealth funds, asset managers, banks and PE/VC; build regional pipeline, represent the company at events, partner on technical evaluations, inform product and GTM strategy, and hire a regional team.

Audit and monitor data labeling outputs, provide actionable feedback, support onboarding and training of annotators, enforce and improve guidelines, escalate workflow issues, and document findings to maintain high-quality human-in-the-loop AI data processes.

Evaluate AI model outputs, perform audit-based reviews, apply and improve guidelines, identify trends and failure modes, document findings, and collaborate with leads and cross-functional teams to refine quality standards.