Job Description:
We are seeking an experienced Machine Learning Engineer to join our high-growth tech team. You will play a key role in developing and deploying ML models within production environments, working closely with software engineers, data scientists, and product managers.
This is not just about writing notebooks - we're looking for someone who can design and implement scalable ML systems, not just scripts. Responsibilities include building and deploying production-grade machine learning models, developing reusable ML pipelines using Python and libraries like scikit-learn, PyTorch or TensorFlow, collaborating with cross-functional teams to integrate ML solutions into real applications, conducting model performance analysis and iterating based on business feedback, automating model training, validation, and deployment using tools like MLflow, Airflow, or Kubernetes, and contributing to code reviews, architecture discussions, and system design.
Required Skills and Qualifications:
* 4+ years of Python development experience (not just scripting - solid OOP, architecture, testing)
* Proven experience deploying ML models into production environments
* Strong understanding of algorithms, data structures, and model evaluation metrics
* Experience with frameworks such as scikit-learn, PyTorch, TensorFlow
* Comfortable working in cloud environments (AWS, GCP or Azure)
* Familiarity with containerization (Docker) and CI/CD for ML workflows
Benefits:
* Hybrid working model (2-3 days onsite)
* Private healthcare
* Pension contribution
* Bonus scheme
* Personal development budget & training
* Collaborative, engineering-first environment
About the Role:
You'll work closely with software engineers, data scientists, and product managers to develop and deploy ML models. Experience with frameworks like scikit-learn, PyTorch, and TensorFlow is a must. Familiarity with cloud environments, containerization, and CI/CD for ML workflows is also desirable.