Jobs at Scale AI

This role involves developing AI applications, focusing on LLMs and agent frameworks, and requires research skills in ML with experience in data strategy.

As a Senior Software Engineer, you'll scale the Scale Generative AI Platform, owning product areas, working across multiple tech stacks, and solving engineering challenges.

This role involves building and optimizing ML systems and frameworks, collaborating with teams to enhance research and development in ML models.

Own the strategy and roadmap for Scale’s enterprise core AI platform, including developer experience, deployment, runtime, security, observability, and customer capabilities. Lead cross-functional alignment with engineering, forward-deployed teams, customers, and business leaders. Define requirements, prioritize investments, measure adoption and outcomes, and productize reusable customer solutions. Build, manage, and coach a high-performing product management team while remaining hands-on with critical product decisions.

Lead initiatives to drive revenue and growth in Generative AI, collaborating with teams and developing strategies aligned with market needs.

Leads and develops a team of Solutions Engineers while personally managing technical wins for strategic consumer accounts. Builds reusable architectures, demos, evaluation frameworks, and sales playbooks for GenAI solutions at consumer scale. Partners with Sales, Product, and Engineering on account strategy, pilots, implementations, and roadmap feedback. Requires strong customer-facing engineering experience, technical leadership, and expertise in high-scale consumer systems, with GenAI or applied machine learning experience preferred.

Lead and grow the enterprise product design team: set design direction, hire and develop designers, drive end-to-end design execution, raise craft standards, contribute to the design system, root decisions in user research, and define human-agent interaction patterns for AI workflows.

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.

Design and develop shared platform systems, foundational data platforms, cloud infrastructure, orchestration, and software delivery tooling. Partner with stakeholders and cross-functional teams to define and deliver features, improve engineering practices, and communicate technical concepts. The role requires expertise in backend systems, distributed systems, public cloud, containerization, databases, orchestration, and CI/CD, with opportunities to support AI-focused products.

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.

Product Manager for Gen AI Platform to drive strategy, execute product roadmaps, and manage cross-functional teams while ensuring quality training data systems for AI models.

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.

Build and own technical enablement for customer-facing engineers, including role-based onboarding, ramp criteria, knowledge-base governance, ongoing technical development, and readiness programs. Partner with engineering, enablement, product, sales, and delivery stakeholders; manage concurrent programs, track milestones, maintain documentation health, identify readiness gaps, and report program outcomes to leadership.

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.

Lead corporate and product communications for Scale’s enterprise AI business: craft narratives for product launches, customer and partner announcements, and executive visibility; develop media strategies and press materials; coordinate joint messaging with partners; build reporter relationships; collaborate across legal, policy, marketing, and social; prepare executives for external engagements; run multi-channel campaigns and monitor coverage to refine communications impact.

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.

The Research Scientist will design methods and experiments for AI control and monitoring, focusing on safety and robustness in advanced AI systems. Key tasks include developing monitoring techniques, researching layered control mechanisms, and collaborating with policymakers and industry experts.