Machine Learning Engineer

Machine Learning Engineer

Location: Barcelona, Hybrid Working (2 days onsite, 3 days remote) Start Date: ASAP End Date: December 2025

Contract type: B2B freelancing

About the Role: Our client are seeking a highly skilled and experienced Machine Learning Engineer to join a project in Barcelona. This is a hybrid role with the flexibility of working two days onsite and three days remotely. You will be responsible for developing and deploying machine learning systems into production, working with various databases and big data tools, and integrating predictive models into larger-scale applications.

Key Responsibilities:

• Develop and deploy machine learning systems into production.
• Work with a variety of relational SQL and NoSQL databases.
• Utilize big data tools such as Hadoop, Spark, and Kafka.
• Develop serverless code with at least one cloud provider solution (AWS, GCP, Azure).
• Program in object-oriented/object function scripting languages like Python, Java, C++, Scala.
• Develop predictive models in a production environment and integrate them into larger applications (MLOps).
• Use Machine and Deep Learning libraries such as Scikit-learn, XGBoost, MXNet, TensorFlow, or PyTorch.
• Leverage GenAI and multimodal AI knowledge via HuggingFace, Llama, VertexAI, AWS Bedrock, or GPT.
• Manage data pipelines and workflows with relevant tools.
• Follow standard software engineering methodologies, including unit testing, test automation, continuous integration, code reviews, and design documentation.
• Work with native ML orchestration systems such as Kubeflow, Step Functions, MLflow, Airflow, TFX.
• Experience with Docker and Kubernetes is a big plus.

Qualifications:

• University or advanced degree in engineering, computer science, mathematics, or a related field.
• 7+ years of experience developing and deploying machine learning systems into production.
• Experience with a variety of relational SQL and NoSQL databases.
• Experience with big data tools: Hadoop, Spark, Kafka.
• Experience with at least one cloud provider solution (AWS, GCP, Azure) and understanding of serverless code development.
• Experience with object-oriented/object function scripting languages: Python, Java, C++, Scala.
• Previous experience developing predictive models in a production environment, MLOps, and model integration into larger-scale applications.
• Experience with Machine and Deep Learning libraries such as Scikit-learn, XGBoost, MXNet, TensorFlow, or PyTorch.
• Exposure to GenAI and solid understanding of multimodal AI via HuggingFace, Llama, VertexAI, AWS Bedrock, or GPT.
• Knowledge of data pipeline and workflow management tools.
• Expertise in standard software engineering methodology, e.g., unit testing, test automation, continuous integration, code reviews, design documentation.
• Working experience with native ML orchestration systems such as Kubeflow, Step Functions, MLflow, Airflow, TFX.
• Relevant working experience with Docker and Kubernetes is a big plus.

If you are passionate about machine learning and meet the qualifications, we would love to hear from you. Apply now or email me to discuss further on [email protected]