Job Description: ML Engineer – Erskine, Scotland or Newcastle, UK Location: Erskine, Scotland or Newcastle, UK Type: Full-Time Remote Work: Hybrid options available Salary: Competitive Benefits About the Role We’re seeking a passionate and skilled Machine Learning Engineer to join our growing team in the Erskine or Newcastle area. You’ll play a key role in designing, developing, and deploying scalable ML solutions across a variety of domains. This is a fantastic opportunity to work with cutting-edge technologies and contribute to impactful projects in a collaborative, innovation-driven environment. Key Responsibilities Design and implement robust machine learning models using modern frameworks and libraries. Collaborate with data scientists, engineers, and stakeholders to translate business requirements into technical solutions. Optimize and deploy models using tools like TensorFlow Serving, TorchServe, ONNX, and TensorRT. Build and manage ML pipelines using MLflow, Kubeflow, and Azure ML Pipelines. Work with large-scale data using PySpark and integrate models into production environments. Monitor model performance and retrain as needed to ensure accuracy and efficiency. Collaborate with cross-functional teams to integrate AI solutions into scalable products Ensure best practices in data engineering and contribute to architectural decisions Contribute to the mentoring and development of junior team members. Support senior team members in identifying and addressing data science opportunities. Required Skills & Experience Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using PySpark. Solid understanding of software engineering principles and version control (e.g., Git). Excellent problem-solving skills and ability to work independently or in a team. Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed data processing using PySpark. Solid understanding of software engineering principles and version control (e.g., Git). Excellent problem-solving skills and ability to work independently or in a team. Typically, 6 years of relevant work experience in industry, with a minimum of 2 years in a similar role. Proficiencies in data cleansing, exploratory data analysis, and data visualization Continuous learner that stays abreast with industry knowledge and technology Why Join Us? Work on impactful AI projects with real-world applications Be part of a collaborative and forward-thinking team Access to continuous learning and development opportunities Flexible working arrangements and a supportive work culture Ready to shape the future of AI? Apply now and bring your expertise to a team that values innovation, creativity, and excellence. 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. Recruitment fraud is a scheme in which fictitious job opportunities are offered to job seekers typically through online services, such as false websites, or through unsolicited emails claiming to be from the company. These emails may request recipients to provide personal information or to make payments as part of their illegitimate recruiting process. DXC does not make offers of employment via social media networks and DXC never asks for any money or payments from applicants at any point in the recruitment process, nor ask a job seeker to purchase IT or other equipment on our behalf. More information on employment scams is available here .