> Markdown version of [/jobs/ext/2067504-staff-machine-learning-engineer](https://www.wearedevelopers.com/jobs/ext/2067504-staff-machine-learning-engineer). Every page supports `.md` or `Accept: text/markdown`. Links point to the HTML versions so they work for humans too. Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md).

---

# Staff Machine Learning Engineer

- **Company:** Super Technologies
- **Location:** Spain
- **Contract:** Permanent contract
- **Skills:** Airflow, Amazon Elastic Compute Cloud, Data Analysis, Python (Programming Language), Machine Learning, Open Source Technology, SQL Databases, Data Streaming, Workflow Management Systems, Feature Engineering, Pytorch, Large Language Models, Cloudformation, Scikit Learn, Information Technology, Xgboost, Apache Kafka, Machine Learning Operations
- **Published:** August 15, 2026
- **Apply:** https://es.trabajo.org/oferta-4111-9aedf3a96b6cf92f148fbe9defa3c56b

## About the Role

influence engineering strategy Proficiency in Python (with libraries such as PyTorch, XGBoost, and Scikit-learn) and SQL Strong experience with machine learning pipelines and orchestration tools such as Airflow, SageMaker Pipelines, or similar Deep understanding of machine learning fundamentals, including experience with Large Language Models (LLMs) and other emerging ML technologies A track record of shipping production-level ML products and maintaining high code quality Excellent problem-solving skills and the ability to scope and disambiguate complex ML projects into clear, achievable milestones Nice to have Familiarity with ML tooling such as MLflow, ZenML, or Metaflow Hands-on experience with AWS services (e.g., EC2, EKS, CloudFormation, Cognito) Exposure to streaming data platforms such as Kafka Contributions to open-source ML projects or publications in ML conferences What we offer Medical / Health Insurance Open Annual Leave Employee Assistance Programme Training &

## Description

involves Identify high-impact ML opportunities and influence stakeholders to prioritise and support these initiatives Design and develop scalable machine learning models - including classifiers, regressors, and rule-based systems - to solve real-world problems Own the full ML lifecycle: from data exploration and feature engineering to model training, evaluation, and deployment Translate complex technical concepts into clear insights for both technical and non-technical stakeholders Set and guide technical direction across ML projects, ensuring alignment with technical best practices and business goals Mentor junior engineers and foster a culture of knowledge sharing and continuous improvement What we are looking for Master's degree (or equivalent) in Machine Learning, Data Science, Statistics, Mathematics, Computer Science, or a related field 7+ years of industry experience building and deploying ML models at scale Proven ability to lead cross-functional technical initiatives and


## Related Videos

- [From Messy Queries to Scalable Systems - How Data Engineering actually works](https://www.wearedevelopers.com/videos/100203-from-messy-queries-to-scalable-systems-how-data-engineering-actually-works)
- [TikTok's Privacy Innovation](https://www.wearedevelopers.com/videos/1036-tiktok-s-privacy-innovation)
- [Photonic Computing: Programming a New Class of AI Accelerators (incl. Live Coding)](https://www.wearedevelopers.com/videos/100196-photonic-computing-programming-a-new-class-of-ai-accelerators-incl-live-coding)
- [Effective Machine Learning - Managing Complexity with MLOps](https://www.wearedevelopers.com/videos/185-effective-machine-learning-managing-complexity-with-mlops)
- [AI Model Management Life Circles: ML Ops For Generative AI Models From Research to Deployment](https://www.wearedevelopers.com/videos/1152-ai-model-management-life-circles-ml-ops-for-generative-ai-models-from-research-to-deployment)
- [Serverless deployment of (large) NLP models ](https://www.wearedevelopers.com/videos/158-serverless-deployment-of-large-nlp-models)

## Related Articles

- [MLops – Deploying, Maintaining And Evolving Machine Learning Models in Production](https://www.wearedevelopers.com/magazine/115-mlops-deploying-maintaining-and-evolving-machine-learning-models-in-production)
- [What Are Large Language Models?](https://www.wearedevelopers.com/magazine/304-what-are-large-language-models)
- [MLOps – What’s the deal behind it?](https://www.wearedevelopers.com/magazine/125-mlops-what-s-the-deal-behind-it)
- [Highest Paying Tech Companies for Developers](https://www.wearedevelopers.com/magazine/220-highest-paying-tech-companies-for-developers)
- [Why Upskilling And Reskilling is Important For Developers](https://www.wearedevelopers.com/magazine/428-why-upskilling-and-reskilling-is-important-for-developers)
- [How to Become an AI Engineer](https://www.wearedevelopers.com/magazine/331-how-to-become-an-ai-engineer)