Mid AI Engineer

TensorOps; Portugal; Remote; EUR 60,000 - 85,000; Full time

Benefits offered by this job

100% Remote Work

Funded certifications: AWS and GCP

Dynamic, High-Impact Projects

International Clients

Urban Sports Club Membership

Monthly Bolt Credits

Company Events & Offsites

Job summary

TensorOps Consulting Services Ltd is seeking a Mid/Senior ML Engineer to guide technical direction across client engagements and mentor junior ML engineers. You will work with clients to move AI systems from prototype to production-grade deployment.

Key responsibilities include designing and deploying ML/LLM systems, working with client teams to translate needs into deliverables, and shaping internal best practices as the team grows. Remote-friendly role with global clients.

Qualifications

• 2+ years in ML/AI engineering or related role (Mid-level) / 5+ years for Senior.
• Strong hands-on Python, writing clean, production-quality code.
• Experience designing, training, optimizing, deploying ML models (PyTorch, TensorFlow, Scikit-learn).
• Experience building GenAI & LLM systems: RAG pipelines, chatbot architectures, and 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 debugging and stakeholder management skills.

Responsibilities

• Design, build, and deploy production ML and LLM-based systems 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

GenAI

LLM systems

LangChain

MLOps

AWS

GCP

Azure

Tools

PyTorch

TensorFlow

Scikit-learn

Job description

About TensorOps

TensorOps 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 200M+ end users daily, partnered with 11 unicorns and NASDAQ-listed companies (including Notion, ServiceNow, JFrog, Seeking Alpha, Armis, and GoCardless), 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 Mid/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.

• 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

You’ll be part of a supportive, fast-growing team that values autonomy, open communication, and continuous learning.

Requirements

• 2+ years of professional experience in Machine Learning, AI Engineering, or a related role (Mid-level) / 5+ years for Senior
• 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

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 GenAI 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