We are seeking a Machine Learning Engineer to design, build, and deploy production-grade ML systems. This is a hands-on technical role requiring a strong foundation in machine learning, data engineering, and modern software development practices.

Responsibilities

• Design, train, and deploy machine learning models for classification, regression, and prediction tasks.

• Build scalable ML pipelines for training and inference, ensuring performance and reproducibility.

• Conduct feature engineering and work effectively with real-world messy data.

• Evaluate models, perform error analysis, and implement improvements based on findings.

• Work with time-based data while preventing data leakage during training and validation.

• Develop deep learning models using PyTorch or TensorFlow.

• Deploy machine learning models to production environments and monitor their performance.

• Implement CI/CD pipelines for ML systems and maintain experiment tracking and versioning (MLflow, Weights & Biases).

• Collaborate with cross-functional teams to design and maintain data pipelines for analytics and model features.

• Write clean, tested, and maintainable Python code following best practices.

• Build and maintain APIs (FastAPI / Flask) for serving models in production.

• Use Git and Docker for version control, containerization, and deployment.

• Work in cloud environments such as AWS, GCP, or Azure for model training, deployment, and monitoring.

• Communicate technical results clearly to technical and non-technical stakeholders.

• Translate ambiguous business challenges into measurable ML problems and own the ML lifecycle end to end.

Requirements

• Strong understanding of supervised machine learning (classification and regression).

• Hands-on experience with ensemble methods (XGBoost, LightGBM, Random Forests).

• Solid foundation in statistics — sampling, probability distributions, and hypothesis testing.

• Proficiency in feature engineering and working with real-world datasets.

• Experience in model evaluation, validation, and performance analysis.

• Familiarity with time-based data and strategies to prevent data leakage.

• Experience building and deploying models using PyTorch or TensorFlow.

• Proven track record in MLOps — deploying, monitoring, and maintaining ML models in production.

• Experience with scalable ML pipelines for both training and inference.

• Knowledge of experiment tracking, model versioning, and ML lifecycle management (MLflow, Weights & Biases).

• Experience implementing CI/CD pipelines for machine learning workflows.

• Advanced programming skills in Python.

• Strong SQL skills for analytics and feature creation.

• Experience handling large datasets using Spark, Dask, or PySpark.

• Familiarity with Docker, Git, and cloud platforms (AWS, GCP, Azure).

• Excellent communication skills and the ability to work effectively in cross-functional teams.

Nice to Have

• Experience with NLP and Transformers (HuggingFace).

• Knowledge of Bayesian modeling and uncertainty estimation.

• Experience with time series forecasting and anomaly detection.

• Familiarity with recommender systems or personalization algorithms.

• Knowledge of Graph ML frameworks (PyG, Neo4j).

• Experience with online or streaming ML (Kafka, Kinesis).

• Familiarity with feature store design and management.

• Experience with distributed training frameworks (Horovod, DeepSpeed).

• Knowledge of A/B testing and experimentation frameworks.

• Domain exposure to finance, risk, healthcare, or insurance.

• Strong system design intuition for scalable ML architectures.

About us

Computacenter is a leading independent technology and services provider, trusted by large corporate and public sector organizations.

We are a responsible business that believes in winning together for our people and our planet.

We help our customers to Source, Transform and Manage their technology infrastructure to deliver digital transformation, enabling people and their business.

Computacenter plc is a public company quoted on the London Stock Exchange (CCC.L) and a member of the FTSE 250. Computacenter employs over 22,000 people worldwide.