About the role
TensorOps is seeking a Mid/Senior AI Engineer to design, build, and deploy production-grade machine learning and LLM-based systems for enterprise clients. The role involves end-to-end technical ownership, from architecture and prototyping to deployment, monitoring, and iteration, while working directly with client engineering and product teams. The engineer will also mentor junior ML engineers, contribute to internal best practices, and represent TensorOps in technical discussions and workshops.
The position requires strong Python skills, experience with ML frameworks such as PyTorch, TensorFlow, or Scikit-learn, and hands-on expertise in GenAI systems including RAG pipelines and LangChain-based applications. Familiarity with MLOps practices and cloud platforms like AWS, GCP, or Azure is essential. This is a fully remote role with opportunities to work on high-impact projects across diverse industries.
Highlights
- 100% remote work with no mandatory office days
- Funded AWS and GCP professional certifications
- Work on cutting-edge ML and GenAI solutions for global clients
- Regular team events and offsites
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