Senior Ml Engineer - Remote, Genai Production

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

About Tensor Ops Tensor Ops is a boutique AI consultancy that bridges strategy and execution, we design and ship production-grade AI systems for enterprise clients, from Fortune 500 companies to fast-growing unicorns. Our work spans agentic AI, LLM fine-tuning, RAG systems, and ML-driven products, deployed on AWS, GCP, and Azure. About Tensor Ops Tensor Ops is a boutique AI consultancy that bridges strategy and execution, we design and ship production-grade AI systems for enterprise clients, from Fortune 500 companies to fast-growing unicorns. Our work spans agentic AI, LLM fine-tuning, RAG systems, and ML-driven products, deployed on AWS, GCP, and Azure.

We've shipped AI systems impacting 200 M+ end users daily, partnered with 11 unicorns and NASDAQ-listed companies (including Notion, Service Now, JFrog, Seeking Alpha, Armis, and Go Cardless), and get 95% of validated ideas into production within two months. We're Google Cloud, AWS, and Cloudflare partners, and we're 100% remote by design.

About the role

We're hiring a Senior 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 (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 Tensor Ops technically in client conversations, workshops, and (optionally) at industry conferences
• You'll be part of a supportive, fast-growing team that values autonomy, open communication, and continuous learning.

Requirements

• 5+ 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., Py Torch, Tensor Flow, Scikit-learn)
• Experience building Gen AI & LLM systems: RAG pipelines, chatbot architectures, and applications using tools like Lang Chain
• 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

What We Offer

• 100% Remote Work : no mandatory office days, work from wherever
• Funded certifications: fully paid AWS and GCP professional certifications
• Dynamic, High-Impact Projects : Work on cutting-edge ML and Gen AI solutions across diverse industries
• International Clients : Collaborate with global organizations and solve real-world challenges at scale
• Urban Sports Club Membership : Supporting your physical and mental wellbeing
• Monthly Bolt Credits : For rides
• Company Events & Offsites : Regular team gatherings to connect, collaborate, and celebrate

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