October 2025
- Job Title: AI/ML Engineer (or Machine Learning Engineer / AI Engineer)
- Location: Barcelona, Spain (hybrid or onsite; many roles offer flexibility)
- Company Type: Tech company, research center (e.g., BSC-CNS), multinational (e.g., ADP, Keysight, Sanofi, Veeva), or startup
- Employment Type: Full-time.
About the Role
We are looking for a passionate AI/ML Engineer to design, build, deploy, and maintain production-grade AI and machine learning solutions. You will work in agile teams to transform data-driven ideas into robust, scalable systems that power business processes, user experiences, or scientific applications. Emphasis is on end-to-end ownership: from data pipelines and model training to cloud/edge deployment, monitoring, and continuous improvement.
Key Responsibilities
- Develop and deploy machine learning models and AI systems using frameworks like PyTorch, TensorFlow, Scikit-learn, Hugging Face, or LangChain.
- Build and optimize data pipelines, feature engineering, and preprocessing workflows to feed models efficiently.
- Fine-tune, train, and evaluate models (including LLMs, generative AI, RAG, agents, computer vision, NLP, or predictive analytics).
- Implement MLOps practices: automated pipelines (CI/CD for ML), model monitoring, retraining, versioning (e.g., MLflow, Kubeflow, SageMaker), and performance tracking.
- Deploy models to production environments (cloud platforms like AWS, GCP, Azure; edge devices; or HPC clusters like MareNostrum).
- Collaborate with data scientists, software engineers, product teams, and stakeholders to define requirements, integrate AI into applications/APIs, and ensure reliability/scalability.
- Conduct experiments, A/B testing, and performance analysis to iterate on models and solve business problems.
- Ensure ethical AI practices, model fairness, explainability, and compliance (e.g., data privacy in regulated sectors like healthcare).
- Mentor junior team members and contribute to best practices in code quality, testing, and documentation.
Required Qualifications
- 3–7+ years of hands-on experience in machine learning engineering or related software development (more for senior levels).
- Strong proficiency in Python (core language); experience with other languages (e.g., Java, C++, Rust) is a plus for performance-critical or embedded systems.
- Solid understanding of ML algorithms, deep learning, statistics, and evaluation metrics.
- Experience deploying models in production (cloud infrastructure, Docker, Kubernetes, APIs like FastAPI/REST).
- Familiarity with MLOps tools and platforms (e.g., MLflow, Kubeflow, Databricks, Vertex AI).
- Bachelor’s or master’s degree in computer science, Data Science, AI, Engineering, or a related quantitative field (PhD advantageous for research-heavy roles).
- Strong problem-solving, analytical skills, and ability to handle large-scale data.
Preferred Skills / Nice-to-Haves
- Expertise in generative AI, LLMs, multi-modal models, agentic systems, or RAG architectures.
- Experience with edge computing, hardware acceleration, low-power inference, or HPC/AI integration.
- Knowledge of cloud services (AWS SageMaker, Google Vertex AI, Azure ML) and distributed systems.
- Domain experience in areas like healthcare, Earth sciences, finance, IoT, semiconductors, or language technologies.
- Contributions to open-source ML projects, publications, or GitHub portfolio demonstrating production ML work.
What We Offer
- Work on impactful AI projects with access to cutting-edge infrastructure (e.g., supercomputers, large datasets).
- Collaborative, innovative environment with opportunities for growth and events participation.
- Competitive salary, flexible working, professional development, and a vibrant Barcelona location.
How to Apply Submit your CV, cover letter, and links to relevant work (e.g., GitHub, publications) through the career’s portal or LinkedIn. We welcome direct applications even if no specific posting is listed reach out via company contact forms for unadvertised roles.
