Design, implement, train, and evaluate a probabilistic foundation model for temporal forecasting, tabular prediction, missing-data completion, and mixed-modality tasks. Run controlled architecture and performance studies, improve scalable PyTorch implementations, and, where relevant, extend synthetic-data generation with richer stochastic dynamics.
You will own the product strategy for the AI infrastructure and orchestration layer, focusing on workload placement, scaling, and lifecycle management. This involves collaborating with engineering pods to define API contracts, resource models, and reliability standards for Kubernetes-based deployments.
The Lead AI Engineer will serve as a strategic advisor to C-level executives, driving the technical vision and successful delivery of complex AI programs. They are responsible for establishing architectural best practices, managing technical risk, and ensuring high customer satisfaction across the professional services portfolio.
The Customer Success Engineer acts as a technical bridge to drive adoption and consumption of GenAI applications for customers. They are responsible for monitoring customer health, facilitating onboarding workshops, and providing technical advocacy to internal product teams.
Collaborate with strategic customers to translate business challenges into AI solutions using the DataRobot platform. Design and deploy a variety of applications including Agentic AI, GenAI chatbots, and predictive machine learning models.
The role involves designing and building enterprise-grade MVP agentic AI applications to demonstrate platform value to prospective customers. You will translate business problems into technical solutions and deliver outcome-oriented demos to accelerate platform adoption.
The Customer Success Engineer drives the adoption and consumption of GenAI applications by serving as the technical bridge between developers and the DataRobot platform. They are responsible for onboarding customers, monitoring product health, and channeling technical feedback to product teams.
Lead the end-to-end delivery of complex Agentic and Generative AI solutions for enterprise customers. Act as a strategic bridge between C-suite stakeholders and technical engineering teams to ensure business goals are met.
The Account Executive is responsible for generating new business by acquiring net-new customers and managing the full sales cycle within assigned territories. They will partner with internal teams to identify GenAI use cases, execute deal negotiations, and ensure a smooth transition to post-sales support.
Drive territory and account sales plans to meet and exceed quotas through value-based selling methodologies. Collaborate with data scientists to deliver technical demonstrations and proof of value sessions to prospective clients.
