Mid-Level AI/ML Engineer

Build the Next Generation of AI Products with TensorOps

TensorOps is an applied-machine-learning studio that helps organisations across Europe and North America design, train, and deploy production-grade GenAI systems. Our team blends research depth with pragmatic engineering, and we’re looking for experienced engineers to help us build and scale our solutions.

What We’re Working On:

• Generative AI applications: Chatbots and Agents
• Traditional Machine Learning: Time Series Forecasting, AdTech, Computer Vision, etc.
• MLOps: Improving ML pipelines at scale

Core Stack:
As we work with many clients, our stack varies, but we often use:

• Python APIs: FastAPI
• Containerization: Docker, Kubernetes
• Model Training & Serving: LightGBM, CatBoost, PyTorch, HuggingFace
• Data Engineering: Pandas, Polars
• LLM Frameworks: LangChain, LangGraph
• Observability: MLFlow, Langfuse
• Cloud Platforms: AWS, GCP
• Search: Elasticsearch, OpenSearch, Solr

The Role

As a Mid-Level Machine Learning Engineer, you will be a key contributor to our project teams, taking ownership of core components and shipping robust AI/ML systems. This is a hands-on role from day one, working on real projects that make a tangible impact.

You will:

• Design, build, and maintain production-grade ML systems, from data ingestion and processing to model deployment and monitoring.

• Develop and fine-tune generative AI models, including LLMs, for specialized tasks. You'll move beyond prototyping to build robust, scalable solutions.

• Architect and implement reliable data pipelines and low-latency inference services using our core stack (FastAPI, Docker, Kubeflow, AWS/GCP).

• Collaborate with senior engineers, researchers, and client stakeholders to translate business problems into technical solutions and deliver tangible value.

• Take ownership of key components of our ML platform, ensuring code quality, performance, and scalability.

About You

• 3+ years of professional experience in a software engineering or machine learning role.

• Strong proficiency in Python and its data science ecosystem (e.g., Pandas, NumPy, Scikit-learn).

• Hands-on experience building and shipping models using at least one major ML framework.

• Proven experience with the practical application of Large Language Models (LLMs). Familiarity with frameworks like LangChain/LangGraph and retrieval-augmented generation (RAG) is a significant plus.

• Solid understanding of software engineering best practices, including version control (Git), testing, CI/CD, and containerization (Docker).

• A BSc/MS in Computer Science, Software Engineering, or a related field, or equivalent practical experience.

Why TensorOps?

• Fully remote (legal residence in Portugal required)
• Real-world projects, rapid feedback loops, and measurable impact
• Mentorship from engineers who have shipped ML systems at scale
• Competitive compensation and growth opportunities - your growth will be based on ownership and performance rather than periodic reviews (which we still do)

Compensation & Perks:

• Yearly salary: €48,000-60,000
• Travel expenses allowance
• Urban Sports Club membership
• Free Professional Certifications