Jobs at TensorOps

Design, build, deploy, and optimize production ML and LLM systems, including RAG pipelines, agentic workflows, fine-tuning, and embeddings. Own technical delivery from architecture through monitoring and iteration, collaborate with client engineering and product teams, mentor junior ML engineers, and help establish internal technical standards and best practices.

Analyze AI model performance, user behavior, and business impact; research machine learning approaches; translate technical findings into business recommendations; create reports, dashboards, and presentations; and support client project discovery. The role requires collaboration with ML engineers and communication with technical and non-technical stakeholders while developing practical expertise in LLMs and generative AI.

Design, build, deploy, monitor, and optimize production machine learning and LLM systems, including RAG pipelines, agentic workflows, fine-tuned models, and embeddings. The role owns technical delivery from architecture through iteration, collaborates with enterprise clients, mentors junior ML engineers, conducts code reviews, and helps establish internal engineering standards and tooling.

Leads client-facing architecture and delivery of production-grade AI/ML systems, including agentic workflows, multi-agent systems, RAG pipelines, search, recommendations, and decision-support tools. Advises clients, leads and mentors ML engineering teams, manages technical engagements, and oversees projects from discovery and architecture through deployment, monitoring, and iteration.

Design, build, deploy, monitor, and optimize production ML and LLM systems, including RAG pipelines, agentic workflows, fine-tuning, and embeddings. Own technical delivery from architecture through iteration, collaborate with client engineering and product teams, mentor junior ML engineers, and help establish internal technical standards and tooling.