Machine Learning Engineer

Job Description:

ML Engineer

Location – Erskine, Newcastle, Farnborough or London (London primarily)

Candidates are required to be eligible for clearance

Are you a curious, innovative engineer who’s passionate about turning data into meaningful impact?

We’re looking for a Machine Learning Engineer to join our growing team—someone who enjoys solving real-world problems, collaborating with supportive colleagues, and building technology that truly makes a difference.

Whether you're early in your ML career or bringing years of experience, this is a place where your ideas will be heard, your voice matters, and your growth is encouraged.

What You’ll Do

In this role, you will have the opportunity to:

Design and build robust machine learning models using leading frameworks. Work closely with data scientists, engineers, and business partners to translate real challenges into smart technical solutions. Deploy and optimize ML models using tools such as TensorFlow Serving, TorchServe, ONNX, and TensorRT. Develop ML pipelines using MLflow, Kubeflow, and Azure ML Pipelines. Work with large-scale datasets using PySpark and bring models into production environments. Monitor model accuracy and performance, ensuring continuous improvement. Collaborate across teams to integrate AI features into scalable products. Contribute to architectural discussions and best practices in data engineering. Mentor junior colleagues and support a culture of knowledge‑sharing. Partner with senior team members to identify new opportunities for data‑driven innovation.

What You’ll Bring

We know that women often apply only when they meet criteria—please apply even if you don't tick every box. If you’re excited about the role, we’d love to hear from you.

Strong Python skills and familiarity with key ML libraries such as:pandas, NumPy, scikit-learnXGBoost, LightGBM, CatBoostTensorFlow, Keras, PyTorch Hands-on experience with model deployment tools:ONNX, TensorRT, TensorFlow Serving, TorchServe Experience with ML lifecycle and pipeline tools:MLflow, Kubeflow, Azure ML Pipelines Experience using PySpark for distributed data processing. Solid grounding in software engineering practices and version control (Git). Strong analytical and problem‑solving abilities. Ability to work well both independently and within a collaborative, cross-functional team. Experience within a similar role in industry. Skills in data cleansing, exploratory analysis, and data visualization. A continuous learning mindset and enthusiasm for staying current with new technologies.

Why You’ll Love Working With Us

Work on impactful, high‑visibility AI projects that deliver real value. Join a collaborative, supportive team that values diverse perspectives. Access learning opportunities, career development, and mentorship. Enjoy flexible working arrangements that support balance and wellbeing. Be part of a culture where innovation, creativity, and authenticity are celebrated.

At DXC Technology, we believe strong connections and community are key to our success. Our work model prioritizes in-person collaboration while offering flexibility to support wellbeing, productivity, individual work styles, and life circumstances. We’re committed to fostering an inclusive environment where everyone can thrive.