Data / Machine Learning Ops Engineer
Role details
Job location
Tech stack
Job description
We are looking for a Machine Learning Ops Engineer to join our growing team. This role is ideal for someone who enjoys solving complex problems, working cross-functionally, and continuously developing their technical expertise in a supportive environment.
If you dont meet every single requirement listed below, we still encourage you to apply. We value potential, curiosity, and a willingness to learn. What Youll Be Doing
- Deploying, monitoring, and scaling machine learning models in production.
- Collaborating with data scientists, engineers, and stakeholders to integrate AI solutions into scalable products.
- Supporting the full ML lifecycle, from experimentation to deployment and optimisation.
- Applying best practices in data engineering and contributing to architectural decisions.
- Using modern MLOps tools and CI/CD approaches to improve reliability and efficiency.
- Contributing to a culture of knowledge-sharing and continuous improvement., We are looking for aMachine Learning Ops Engineerto help operationalise machine learning across Affinity Water on a 24 month FTC. Youll work with data scientists, engineers, architects, and stakeholders to deploy, monitor, and maintain ML models in robust, scalable, and..., We are looking for a Machine Learning Ops Engineer to help operationalise machine learning across Affinity Water on a 24 month FTC. Youll work with data scientists, engineers, architects, and stakeholders to deploy, monitor, and maintain ML models in robust, scalable, and...
Requirements
Are you passionate about bringing machine learning solutions into real-world production environments? Do you enjoy collaborating with others to build scalable, reliable systems?, * Strong Python skills and familiarity with ML libraries such as Pandas, NumPy, and scikit-learn.
- Experience with frameworks such as TensorFlow, Keras, or PyTorch.
- Exposure to gradient boosting tools such as XGBoost, LightGBM, or CatBoost.
- Experience with model deployment tools (e.g., ONNX, TensorRT, TensorFlow Serving, TorchServe).
- Familiarity with ML lifecycle tools such as MLflow, Kubeflow, or Azure ML Pipelines.
- Experience working with distributed data processing (e.g., PySpark) and SQL.
- Understanding of software engineering best practices, including version control (Git).
- Knowledge of CI/CD principles in ML environments.
- Experience with cloud-native ML platforms is advantageous.
What Were Looking For
- A collaborative mindset and strong communication skills.
- A thoughtful, structured approach to problem solving.
- A commitment to continuous learning and professional growth.
- The confidence to contribute ideas while valuing diverse perspectives.
Benefits & conditions
Why Join Us?
- Work on meaningful AI projects with real-world impact.
- Join a supportive, forward-thinking team that values inclusion and diverse perspectives.
- Access structured learning, mentoring, and career development opportunities.
- Flexible hybrid working arrangements.
- A workplace culture that supports wellbeing and work-life balance.
What We Offer
- Competitive salary.
- Pension scheme.
- DXC Select comprehensive benefits package including private medical insurance, gym membership, and more.
- Perks at Work discounts on technology, groceries, travel and more.
- DXC incentives recognition tools, employee lunches, and regular social events.
Ready to Shape the Future of AI?
We are committed to building diverse teams and creating an inclusive environment where everyone can thrive. If this role excites you, wed love to hear from you., £90,000
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