Machine Learning Engineer
SKILLS
FULL DESCRIPTION
Summary
[Employer hidden — view at passion-project.co.uk] is hiring a Machine Learning Engineer to design, develop, and deploy machine learning models for real-world problems. The role involves building scalable data pipelines, working with various data types, conducting feature engineering, collaborating with cross-functional teams, and leveraging MLOps tools.
- Designing, developing, and deploying machine learning models for real-world problems
- Building scalable data pipelines and integrating models into production systems
- Working with structured and unstructured data across domains (e.g., text, image, tabular)
- Conducting feature engineering, model evaluation, and hyperparameter tuning
- Collaborating with product, data, and engineering teams to deliver end-to-end ML solutions
- Leveraging MLOps tools for versioning, deployment, and monitoring of models
- Solid experience with ML algorithms, model development, and applied data science
- Proficiency in Python and ML libraries (e.g., scikit-learn, XGBoost, LightGBM)
- Hands-on experience with cloud services (AWS, GCP, or Azure) and containerization (Docker/Kubernetes)
- Familiarity with MLOps tools like MLflow, SageMaker, or Vertex AI is a plus
- Degree in Computer Science, Machine Learning, Data Science, or related field (MSc or PhD preferred)
- Strong analytical mindset and ability to translate business needs into ML solutions
Machine Learning Engineer
By DEVITECHNOLOGIES / 2 May 2025
- Full Time
- United Kingdom (Remote/Hybrid Options Available)
- Posted 3 months ago
- Competitive, aligned with top industry standards GBP / Year
Website [Employer hidden]
What You’ll Be Working On: Designing, developing, and deploying machine learning models for real-world problems Building scalable data pipelines and integrating models into production systems Working with structured and unstructured data across domains (e.g., text, image, tabular) Conducting feature engineering, model evaluation, and hyperparameter tuning Collaborating with product, data, and engineering teams to deliver end-to-end ML solutions Leveraging MLOps tools for versioning, deployment, and monitoring of models
What We’re Looking For: Solid experience with ML algorithms, model development, and applied data science Proficiency in Python and ML libraries (e.g., scikit-learn, XGBoost, LightGBM) Hands-on experience with cloud services (AWS, GCP, or Azure) and containerization (Docker/Kubernetes) Familiarity with MLOps tools like MLflow, SageMaker, or Vertex AI is a plus Degree in Computer Science, Machine Learning, Data Science, or related field (MSc or PhD preferred) Strong analytical mindset and ability to translate business needs into ML solutions
To apply for this job email your details to [contact hidden]