Senior GenAI ML Engineer - Production Systems (Remote)

Tensorops Consulting Services Ltd; Viseu; Remote; EUR 70,000 - 100,000; Full time

Benefits offered by this job

100% Remote

AWS Certification

GCP Certification

High-Impact Projects

International Clients

Urban Sports Club

Bolt Credits

Team Offsites

Job summary

Tensor Ops is hiring a Senior ML Engineer to drive technical direction across client engagements and mentor a growing team. You will design, build, and deploy production ML and LLM-based systems, from prototyping to production-grade deployment, while working directly with client teams to translate business needs into scalable solutions.

You'll lead end-to-end delivery, optimize performance, and help establish internal standards as the team expands.

Qualifications

• 5+ years of professional experience in Machine Learning or AI Engineering.
• Strong Python programming with production-quality code.
• Experience designing, training, optimizing, and deploying ML models end-to-end.
• Experience deploying and scaling ML systems on cloud platforms (AWS/GCP/Azure).

Responsibilities

• Design, build, and deploy production ML and LLM-based systems for enterprise clients.
• Own end-to-end technical delivery from architecture to deployment and monitoring.
• Collaborate with client engineering/product teams to translate business needs into solutions.
• Mentor ML engineers, provide code reviews and knowledge sharing.
• Help shape internal tooling, standards, and best practices.

Skills

Python

ML Engineering

Gen AI

LLM systems

MLOps

Client collaboration

Tools

PyTorch

TensorFlow

Scikit-learn

LangChain

CI/CD for ML

Job description

Tensor Ops is hiring a Senior ML Engineer to drive technical direction across client engagements and mentor a growing team. You will design, build, and deploy production ML and LLM-based systems, from prototyping to production-grade deployment, while working directly with client teams to translate business needs into scalable solutions.

You'll lead end-to-end delivery, optimize performance, and help establish internal standards as the team expands.