Machine Learning Engineer
New Today
Position Overview
- We are seeking a highly skilled Machine Learning Engineer to design, build, deploy, and optimise machine learning models that power data-driven products and business solutions.
- This role bridges data science and software engineering, focusing on production-ready ML systems, scalability, and performance.
- The ideal candidate has strong experience in Python, ML frameworks, data pipelines, and cloud platforms, and is comfortable working in a fully remote, collaborative environment within the UK.
Key Responsibilities
1. Machine Learning Model Development
- Design, develop, train, and evaluate machine learning models for prediction, classification, recommendation, or automation use cases.
- Apply supervised, unsupervised, and deep learning techniques as appropriate.
- Perform feature engineering, model tuning, and validation to improve accuracy and performance.
2. Productionisation & Deployment
- Deploy ML models into production using scalable, reliable architectures.
- Build and maintain APIs or batch pipelines for model inference.
- Monitor model performance, data drift, and retraining needs.
3. Data Engineering & Pipelines
- Collaborate with data engineers to design efficient data ingestion and transformation pipelines.
- Work with structured and unstructured data from databases, APIs, and data lakes.
- Ensure data quality, reproducibility, and versioning.
4. MLOps & Automation
- Implement MLOps practices including CI / CD for ML, model versioning, and experiment tracking.
- Use tools such as MLflow, Kubeflow, SageMaker, Vertex AI, or Azure ML.
- Automate model training, testing, deployment, and monitoring workflows.
5. Cloud & Infrastructure
- Build ML solutions on cloud platforms such as AWS, Azure, or GCP.
- Use containerization and orchestration tools (Docker, Kubernetes).
- Optimize compute costs and performance for training and inference workloads.
6. Collaboration & Stakeholder Engagement
- Work closely with Data Scientists, Product Managers, Software Engineers, and Analysts.
- Translate business requirements into scalable ML solutions.
- Communicate model behaviour, limitations, and results clearly to non-technical stakeholders.
7. Research & Continuous Improvement
- Stay current with advancements in machine learning, AI, and data science.
- Evaluate new algorithms, tools, and frameworks for potential adoption.
- Contribute to best practices, documentation, and knowledge sharing.
Required Skills & Experience
Core Technical Skills
- 3+ years of experience in Machine Learning, Data Science, or related roles.
- Strong programming skills in Python.
- Experience with ML frameworks : TensorFlow, PyTorch, scikit-learn, XGBoost.
- Solid understanding of ML algorithms, statistics, and evaluation metrics.
- Experience deploying ML models into production environments.
Data & Engineering Skills
- Strong SQL skills and experience working with large datasets.
- Familiarity with data processing tools (Pandas, NumPy, Spark).
- Experience building APIs (FastAPI, Flask) for ML services.
- Location:
- Manchester, England, United Kingdom
- Salary:
- £150,000 - £200,000
- Job Type:
- FullTime
- Category:
- Engineering
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