Remote ML Engineer - Production GenAI for Enterprises

TensorOps Consulting Services Ltd; Portugal; Remote; EUR 50,000 - 70,000; Full time

Benefits offered by this job

Remote work

Certifications funded

High-impact projects

International clients

Urban Sports Club

Bolt credits

Offsites

Job summary

TensorOps is hiring a Mid-Level ML Engineer to contribute to technical direction across client engagements and mentor a growing team of junior ML engineers. You’ll work directly with clients, taking AI systems from prototype to production-grade deployment.

In this role, you will design, build, and deploy production ML and LLM-based systems and own technical delivery end-to-end, collaborating with client teams to translate business needs into scalable solutions.

Qualifications

• 2+ years of professional experience in Machine Learning, AI Engineering, or a related role.
• Strong hands-on skills in Python, writing clean, efficient, well-documented, production-quality code
• Proven experience designing, training, optimizing, and deploying ML models independently (e.g., PyTorch, TensorFlow, Scikit-learn)
• Experience building GenAI & LLM systems: RAG pipelines, chatbot architectures, and applications using tools like LangChain
• Familiarity with MLOps & production ML practices: model versioning, monitoring, CI/CD for ML workflows
• Experience deploying and scaling ML systems on AWS, GCP, or Azure
• Strong performance optimization and debugging skills (diagnosing complex issues and improving system reliability and efficiency)
• Experience working with stakeholders or clients is a plus

Responsibilities

• Design, build, and deploy production ML and LLM-based systems (RAG, agentic workflows, fine-tuning, embeddings) for enterprise clients
• Own technical delivery end-to-end: from architecture and prototyping to deployment, monitoring, and iteration
• Work directly with client engineering and product teams to translate business needs into scoped, shippable technical solutions
• Mentor and support other ML engineers on the team — code reviews, technical guidance, and knowledge sharing
• Help shape internal best practices, tooling, and technical standards as the team grows
• Represent TensorOps technically in client conversations, workshops, and (optionally) at industry conferences

Skills

Python

Production-grade code

Documentation

Client interaction

Tools

PyTorch

TensorFlow

Scikit-learn

LangChain

CI/CD for ML workflows

Job description

TensorOps is hiring a Mid-Level ML Engineer to contribute to technical direction across client engagements and mentor a growing team of junior ML engineers. You’ll work directly with clients, taking AI systems from prototype to production-grade deployment.

In this role, you will design, build, and deploy production ML and LLM-based systems and own technical delivery end-to-end, collaborating with client teams to translate business needs into scalable solutions.