Top Natural Language Processing Jobs in Boston, MA

The Applied AI Workflow Scientist, Sr. Manager drives the application of AI and LLMs in scientific workflows, collaborating with various stakeholders to improve operational efficiency in Immunology and Inflammation.

Leads AI strategy and technical direction for applied AI in Inflammation & Immunology, overseeing portfolio development, partnerships, and governance standards to improve scientific decision-making.

The role involves designing and deploying AI systems for clinical operations, developing models for decision-making, and ensuring AI implementation aligns with data governance standards. Responsibilities include collaborating across teams, enhancing operational efficiency, and advancing AI applications in a regulated environment.

As an AI Product Specialist, you'll drive market expansion and customer engagement by defining strategies for AI product growth, conducting market analyses, and supporting sales teams. You'll leverage AI expertise and guide product development and competitive positioning while collaborating across teams to enhance Kensho's AI solutions.

As a Backend Software Engineer II, you will develop, maintain, and improve software, focusing on reliable and performant APIs while collaborating with teams across the company.

The Cloud Engineer will develop and maintain cloud infrastructure, oversee deployment of cloud services, and ensure compliance with security guidelines. Candidates should possess strong communication skills and be eager to learn new technologies. Experience with AWS, Azure, GCP, Terraform, and Agile development is required.

Responsible for designing and implementing training programs for Sales and Customer Success teams, improving performance through metrics, and collaborating with departments for training needs.

As a Billing & Analytics Software Engineer, you'll design and maintain the billing pipeline, integrate billing systems, and develop customer-facing analytics dashboards to support revenue recognition and operational observability.

The role involves researching and developing large language models (LLMs) with a focus on transformer architecture, data curation, distributed training, and optimization. Responsibilities include conducting experiments, collaborating with teams, and staying updated on deep learning advancements.

The Account Executive at Deepgram is responsible for building a sales pipeline, exceeding targets, collaborating with teams, and understanding customer needs to sell the voice AI platform.

Lead a small team to define and execute website content strategy across multiple product sites, drive content roadmaps and operational excellence, partner with cross-functional stakeholders, and contribute hands-on to high-priority content. Scale content production using CMS, AI-assisted workflows, freelancers, and strong quality-control processes to support acquisition, conversion, and product storytelling.

Own and build Hebbia's APAC sales presence from Singapore: manage full enterprise sales cycles, develop relationships with institutional investors, shape regional GTM strategy, represent the product at events, and hire a regional team.

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.

Lead the development of cybersecurity training content by managing a team, overseeing complex projects, and ensuring high-quality learning experiences.

The Director of Demand Generation leads global pipeline strategies, manages demand generation initiatives, and oversees budget allocation while ensuring alignment with sales and reporting on key performance metrics.

Design, implement, and maintain CI/CD pipelines and infrastructure as code (Terraform). Deploy, manage, and monitor containerized applications and production Kubernetes clusters in AWS. Administer GitHub workflows, troubleshoot infrastructure and application issues, and collaborate with development teams to improve developer toolsets, SDLC processes, security, reliability, and performance.