The Customer Support Engineer will serve as the primary point of contact for platform users, resolving technical issues and routing complex requests to the appropriate teams. They will also manage support queues, document bugs, and collaborate with enterprise customers to ensure platform success.
You will own the data transformation layer and warehouse, ensuring consistent metric definitions across the organization. Additionally, you will lead a new data sub-team, hire key engineering talent, and implement agentic engineering practices.
You will own the architecture and technical strategy for internal tools that support LILT's Applied AI benchmarking business. This involves building and maintaining reliable, production-ready infrastructure and automation to enable efficient data-quality and workforce management workflows.
You will lead complex benchmark transformations and data deliverables while architecting workflows for LLMs and multimodal models. You will act as the CEO of your customer's business to drive success and bridge the gap between research, engineering, and production teams.
You will own the connector strategy and roadmap, ensuring reliable and scalable integrations between LILT and enterprise content systems. You will lead the full product lifecycle from discovery through launch, while collaborating with engineering and customer-facing teams to resolve technical challenges.
The Project Manager will oversee the end-to-end lifecycle of large-scale multilingual data collection and LLM evaluation initiatives. They are responsible for managing data pipelines, monitoring performance KPIs, and coordinating global teams of annotators to ensure high-quality AI development.
Manage large-scale multilingual data collection, human-in-the-loop workflows, and LLM evaluation initiatives. Coordinate with engineering and AI specialists to translate technical requirements into high-throughput data pipelines and measurable delivery plans.
Serve as the technical co-pilot for account teams, managing the customer journey from pre-sales scoping to post-sales deployment. Build reference architectures and demos while providing consultative assistance on AI-driven translation and localization implementations.
