Top Tech Jobs & Startup Jobs in NYC, NY

Lead Scale’s Connectivity engineering team, owning architecture, strategy, and development of API integrations, distributed systems, and data-platform capabilities. Build and ship end-to-end product features, collaborate with internal and external stakeholders, manage the full product lifecycle, and deliver high-quality experiments rapidly. The role also includes mentoring engineers, influencing team culture and processes, and translating business and product ideas into scalable engineering solutions.

Leads product design for Scale’s enterprise AI data business, covering 0-to-1 initiatives and established products. Designs user flows, wireframes, mockups, prototypes, dashboards, data visualizations, editors, and forms for desktop web applications. Partners with product, engineering, data science, and operations teams; advocates for users; contributes to the design system; identifies product gaps; and drives solutions in a fast-paced, ambiguous environment.

Manage and grow a large global contributor community for Scale’s Generative AI business. Develop engagement, retention, communications, feedback, and dispute-resolution strategies; oversee community platforms, virtual events, sentiment monitoring, and contributor messaging. Use metrics and feedback to improve operations and product strategy, coordinate cross-functional stakeholders, remove blockers, and maintain cohesive communications. The role also includes managing at least one direct report and executing operational initiatives directly.

Own the technical foundation for building, packaging, executing, verifying, and scaling reinforcement learning environments. Design sandboxed execution, rollout orchestration, trajectory capture, verifier frameworks, environment versioning, and authoring tools. Build high-throughput infrastructure and reliable reward signals, instrument real applications, develop task suites, and defend against reward hacking. Provide staff-level technical leadership across engineering and research teams while shipping complex production systems.

Research and develop novel post-training methods such as SFT, RLHF, reward modeling, and preference optimization for text and multimodal LLMs. Analyze model behavior, improve alignment and generalization, mitigate bias, enhance robustness, and publish findings at leading AI conferences. Collaborate with engineers, researchers, and foundation model labs to establish data-driven AI development practices and provide technical and strategic guidance.

Conduct research on evaluating frontier large language models and AI agents. Analyze model behavior, diagnose capability, reasoning, robustness, and alignment failures, and develop benchmarks for text and multimodal systems. Apply post-training techniques such as supervised fine-tuning, RLHF, and reward modeling to connect failures with training interventions. Collaborate with AI labs, define evaluation best practices, translate findings into technical strategy, and publish research at major conferences.

Lead cross-functional initiatives to drive multimillion-dollar revenue: partner with product and engineering, own data-labeling operations for strategic projects, provide executive updates, and solve high-impact operational and product problems.

Own Scale’s end-to-end commercial acquisition of proprietary training data for AI environments. Identify high-value data domains and organizations, develop partnership and pricing structures with Legal, conduct outreach, negotiate and close transactions, and translate dataset requirements between commercial and Research teams. Build the acquisition function from the ground up, converting initial hands-on learnings into a repeatable pipeline.

Lead development of generative AI platforms for U.S. government, ensuring ethical deployment and compliance, managing the full product lifecycle, and engaging stakeholders.

Design and scale multi-cloud infrastructure for an enterprise Generative AI platform. Build integrations with customer cloud/data environments, collaborate with product and customers, deliver experiments to production, and maintain platform reliability and performance.