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Lead the deployment of Dynamo AI clusters in customer environments, ensuring scalable and secure solutions while engaging directly with clients

Lead the engineering team in designing, developing, and deploying reliable ML services while collaborating with cross-functional teams to optimize AI solutions.

As a Senior Kubernetes Engineer, you will lead enterprise customer onboarding, manage deployment of Kubernetes clusters, and ensure secure, scalable AI systems in production environments.

Lead the ML privacy vertical, developing algorithms to prevent data leakage, conducting evaluations, and collaborating with engineers to deliver applications.

Design and maintain ML code for LLM safety, implement techniques for robust evaluation, and collaborate with product and engineering teams.

The Technical Product Manager will oversee platform strategy, deployment, security, and compliance while collaborating with engineering and customer success teams.

The role involves owning an LLM safety domain, generating synthetic data, training LLMs, conducting benchmarking, and developing techniques for safer models. Co-author research papers with the team.

The Customer Success Senior Manager will lead the Customer Success team, manage client relationships, drive customer retention, and oversee onboarding and adoption of AI solutions.

Lead and build the Sales Engineering team, drive technical sales strategies, and ensure customer satisfaction through AI solutions integration.

Manage all accounting operations, ensure compliance, prepare financial statements, coordinate reporting, support budgeting, and develop accounting policies.