Jobs at Pangram Labs

Build machine learning infrastructure spanning large-scale data generation, distributed multi-GPU model training, training and inference optimization, and production LLM deployment and monitoring. The role also contributes to AI detection research and innovation. Candidates need strong Python and modern ML framework skills, deep learning experience, and knowledge of transformers and LLM fundamentals.

Own and optimize Pangram’s HubSpot CRM, revenue workflows, forecasting, dashboards, pipeline analytics, and data hygiene. Partner cross-functionally with Sales, Marketing, Finance, and Operations to automate processes, reduce administrative work, identify growth opportunities, and support executive, investor, and business reviews. This is a full-time, on-site role in Brooklyn.

Manage and qualify inbound sales opportunities from website visitors, conferences, B2C users, and other channels. Conduct discovery calls, understand prospect needs and buying processes, maintain accurate sales data, partner with Account Executives on handoffs, improve sales messaging and processes, and share customer and market feedback. The role is designed for growth toward an Account Executive position.

Own the full sales cycle for inbound education opportunities, from qualification and discovery through product demonstrations, pilots, proposals, negotiations, and closing. Maintain pipeline and forecasts, coordinate customer transitions, improve sales messaging and processes, and share market feedback with leadership. The role requires strong communication, organization, relationship-building, quota performance, and the ability to learn a technical product in an early-stage, onsite environment.

Conduct research on frontier AI detection and related topics under mentorship, selecting projects across adversarial robustness, interpretability, mixed authorship, new architectures, multimodal detection, AI-generated training data, and agentic AI detection. Interns are expected to pursue publishable research for a major AI conference and may propose original topics.

Own and evolve Pangram’s visual identity across brand, web, product, and marketing touchpoints. Design and ship the main website, brand experiences, campaign assets, social content, sales collateral, event materials, and merchandise. Develop brand guidelines and documentation, collaborate with founders and cross-functional teams, integrate branding into product experiences, and maintain visual quality across the organization.

Lead Pangram Labs’ B2B growth marketing strategy, defining ideal customers and qualified leads, generating demand through paid, SEO, content, events, and outbound support, and improving conversion through landing pages, email nurturing, and retargeting. Partner with sales on lead handoffs and collateral, measure pipeline and cost per lead across channels, and reallocate budget toward the most effective growth opportunities.

Owns end-to-end product development across consumer and B2B experiences, including user-facing interfaces, microservices, APIs, instrumentation, and observability. Collaborates with design, product, go-to-market, and research teams to turn prototypes into polished products using machine learning technology. Responsibilities include code review, feature delivery, and maintaining high engineering quality.

Build customer-facing software solutions, custom integrations, deployments, and infrastructure. Own bugs and feature requests, support API onboarding, debug customer issues, communicate through Slack, and create technical documentation. Collaborate with engineering and product teams to identify recurring issues and inform the roadmap.

Own and resolve customer support cases across email, chat, and other channels. Troubleshoot product issues, identify trends, coordinate with Product and Engineering on bugs, and maintain support systems, playbooks, documentation, and customer-facing content. The role also supports compliance questionnaires, vendor onboarding, and procurement requests while helping establish the company’s growing support function.

Conduct research and engineering for AI-generated content detection models. Responsibilities include training large-scale deep learning models, creating synthetic datasets, developing novel detection methods, researching adversarial robustness and interpretability, publishing technical work, deploying models, building infrastructure, and collaborating with engineering and product teams.

Design, build, and scale backend services and APIs powering Pangram’s AI detection platform. Own AWS infrastructure, reliability, performance, observability, data pipelines, caching, and production model-serving integrations. Resolve scaling bottlenecks, establish engineering best practices for testing and deployment, and improve incident response. Collaborate with frontend and machine learning teams in a high-autonomy, on-site role.

Manage inbound enterprise sales opportunities from qualification through close. Conduct discovery calls and product demonstrations, coordinate pilots, develop proposals, negotiate commercial terms, close new business, and maintain accurate pipeline forecasts. Partner with Customer Success on account transitions, improve sales messaging and processes, and provide customer and market feedback to leadership. The role requires strong communication, organization, relationship-building, quota performance, and the ability to learn a technical AI product.

Own product direction across web, Chrome extension, integrations, and API surfaces. Prioritize engineering work, translate product vision into specifications, lead launches, triage customer feedback, conduct user research, and coordinate engineering, growth, and leadership. The role requires strong product management experience, consumer or prosumer exposure, technical fluency with AI, customer-facing skills, and proficiency with AI automation and design tools.

Build machine learning infrastructure spanning large-scale data generation, distributed multi-GPU training, model optimization, and production LLM inference. The role also contributes to ML research and innovation, requiring strong Python and modern ML framework skills, transformer and LLM knowledge, and comfort bridging research and engineering. Preferred experience includes CUDA, distributed training, vLLM, Spark, Beam, Airflow, MLOps, DevOps, and cloud infrastructure.