Work with XGBoost, Random Forests, LSTM, transformers, LLMs, Python, R, SQL, Azure, Git, PowerBI, and Looker. You will drive business outcomes by applying AI/ML to solve problems in NLP, computer vision, and recommender systems for a global academic publisher.

Build and scale data pipelines for large video generation models using AWS S3, DynamoDB, Kubernetes, Python, and PyTorch. You will design annotation workflows across MTurk and Prolific, and train smaller supporting models for data filtering and quality assessment. Cantina Labs is a social AI company developing real-time character models.

Sage★3.5 (901)· London

You will apply Python, R, SQL, XGBoost, Random Forests, LSTM, transformers, and Azure services to solve problems in NLP, computer vision, and recommender systems. The team builds AI/ML models to drive commercial impact for Sage, a global academic publisher of books, journals, and library resources.

You will use Python, R, SQL, Git-based platforms, Azure services, PowerBI, and Looker to build AI/ML solutions—including NLP, Computer Vision, recommender systems, and LLMs—for a global academic publisher of books, journals, and library resources.

Design and build an ML system for Advert Classification using MLOps, LLMs, Azure/AWS, and computer vision. Lead a team of Data Scientists through the ML lifecycle, experiment tracking, and production deployment. Provide technical direction and mentor engineers while shaping ML workflows.

JD.COM★3.8 (53)· London

Use Python, R, or Scala; ML frameworks (TensorFlow, PyTorch, Scikit‑learn); data‑viz tools (Tableau, Power BI); and big‑data platforms (Spark, Hadoop) with cloud ML pipelines (AWS Sagemaker, GCP Vertex AI, or Azure ML). You will build predictive models and analytics for personalization, recommendation, and customer segmentation on JD.com’s international e‑commerce operations.

Sainsbury’s★3.5 (16k)· London

Design and build ML systems for Advert Classification using modern ML tooling, LLMs, MLOps, and cloud platforms (Azure/AWS). You will lead a team of Data Scientists, driving the ML lifecycle, model evaluation, and production deployment.

You will work with Python, PyTorch, TensorFlow, MLOps, CI/CD, and cloud-based AI systems. You will lead the technical strategy for production ML systems that transform raw sports data and live video into real-time insights and personalised fan experiences. You will mentor engineers and data scientists while owning technical direction and delivery.

McKinsey & Company★4.2 (952)· London

You will work with Python, pandas, numpy, scikit-learn, PyTorch/TF/Keras, LangChain, GitHub, and optional R/C++. You join McKinsey’s global Scientific AI team applying AI to therapeutics, chemicals, and materials (small molecules, proteins, mRNA) to build models and support client delivery.

Amazon★3.5 (56k)· London

As an Applied Science Intern, you will work with machine learning, deep learning, generative AI, large language models, speech technology, robotics, computer vision, optimization, operations research, quantum computing, and formal methods, using Java, C++, or Python. You will design and develop end-to-end systems, working with Amazon scientists to create algorithms and models that are deployed into production.

Softwire, a UK digital consultancy, seeks a Senior Data Scientist with expertise in Python, PyTorch/TensorFlow/Keras, Scikit-learn, MLflow, and cloud platforms (Azure ML/SageMaker/Databricks) to design and deliver end-to-end data science projects across predictive analytics, computer vision, NLP, and MLOps for public and private sector clients. The role combines hands-on technical work with consultancy—scoping, designing and owning technical delivery with limited oversight—plus contributions to internal capability growth and methodology development, with no formal line management responsibilities.

JPMorgan★3.9 (20k)· London

You'll work with PyTorch, deep learning frameworks (transformers, CNNs, autoencoders), NLP techniques, Docker, cloud platforms (Azure/AWS/GCP), MLOps tools, and DAG-based pipelines to build scalable machine learning services for JPMorgan's Commercial & Investment Bank. The team develops AI-powered products that automate financial processes, enhance decision-making, and optimize business operations across the bank. This is an individual contributor role with optional management opportunities.