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Agent guide: [/agents.md](https://www.wearedevelopers.com/agents.md). --- # Enterprise Architect - **Company:** HCLTech - **Location:** London, UK - **Experience:** Expert - **Contract:** Permanent contract - **Skills:** Amazon Web Services, Computer Vision, Microsoft Azure, Big Data, Cloud Computing, Statistical Hypothesis Testing, Python (Programming Language), Machine Learning, Natural Language Processing, NumPy, Tensorflow, Standard Sql, Azure Machine Learning, Data Processing, Feature Engineering, Pytorch, Transfer Learning, Large Language Models, Apache Spark, Deep Learning, Model Validation, Pandas, Scikit Learn, Information Technology, Machine Learning Operations, Unsupervised Learning - **Published:** September 8, 2026 - **Apply:** https://www.collegerecruiter.com/job/2856354196-enterprise-architect ## About the Role HCLTech is looking for a highly talented and self- motivated Enterprise Architect / Solutions Director (Data scientist) to join it in advancing the technological world through innovation and creativity., * 15+ years of total professional experience, including * 8+ years of hands-on experience in machine learning and data science * Advanced degree (Master's or PhD preferred) in Computer Science, Statistics, Mathematics, Engineering, or related quantitative discipline * Proven experience building and deploying advanced ML and deep learning models in enterprise environments * Deep understanding of algorithm selection, model complexity trade-offs, and overfitting/underfitting dynamics * Strong proficiency in Python and ML ecosystems (scikit-learn, pandas, NumPy) * Experience with deep learning frameworks (PyTorch or TensorFlow) * Practical knowledge of deep learning architectures (CNNs, RNNs, Transformers) and when to apply them * Strong SQL and data manipulation capabilities * Experience working with large-scale datasets and distributed compute frameworks (e.g., Spark) * Demonstrated ability to independently lead technical ML solution design * Experience working in client-facing delivery environments * Exposure to cloud-based ML platforms (AWS, Azure, or GCP) * Experience in NLP, Computer Vision, time-series forecasting, or optimization. * Experience with fine-tuning large language models or foundation models * Familiarity with ML lifecycle management and monitoring practices. ## Description We are seeking senior-level Data Science Leader to lead the design and delivery of advanced machine learning solutions for enterprise clients across Europe. This role requires deep expertise in machine learning, statistical modelling, and modern deep learning architectures. You will be responsible for structuring complex problems, selecting appropriate modelling approaches, guiding architectural decisions, and delivering scalable ML solutions that generate measurable business impact. This is a hands-on technical leadership role within delivery, suited for individuals who combine strong theoretical grounding with practical enterprise implementation experience., * Lead end-to-end machine learning solution delivery for complex enterprise use cases * Translate ambiguous business challenges into structured ML problem statements and solution architectures * Design, develop, and optimise advanced machine learning models including: * Supervised and unsupervised learning * Deep learning architecture * Optimisation and probabilistic models * Evaluate and select appropriate algorithms based on data characteristics, performance trade-offs, scalability, and interpretability requirements * Apply knowledge of deep learning architectures such as: * CNNs for vision use cases * RNNs / LSTMs / GRUs for sequential data * Transformer architectures for NLP and structured data * Fine-tuning and transfer learning approaches * Drive experimentation frameworks, hypothesis testing, model validation, and statistical rigor * Ensure robustness, generalisation, bias mitigation, and explainability in deployed models * Provide technical direction on feature engineering strategies and model performance enhancement * Collaborate with engineering teams to transition models into scalable production systems * Mentor data scientists and uphold modelling standards, documentation, and reproducibility best practices * Contribute to reusable ML frameworks, accelerators, and innovation initiatives ## Related Videos - [Architecting the Future: Leveraging AI, Cloud, and Data for Business Success](https://www.wearedevelopers.com/videos/1096-architecting-the-future-leveraging-ai-cloud-and-data-for-business-success) - [Advanced Typing in TypeScript](https://www.wearedevelopers.com/videos/496-advanced-typing-in-typescript) - [Vectorize all the things! 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