11 of 11 Remote Keras Jobs

Engineer to join our growing teams in Erskine or Newcastle. Key Responsibilities 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 More ❯

and PyTorch. Programming: Solid experience in Python and SQL. Experience with R is a nice-to-have. ML and AI: Practical experience using ML modeling libraries like Scikit-Learn, Keras, Tensorflow, PyTorch and similar Generative AI: Some hands-on experience with LLMs for prompt engineering or agents is preferred Cloud Expertise: Building, deploying and monitoring models on cloud like Azure More ❯

Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings into actionable insights More ❯

Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings into actionable insights More ❯

Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings into actionable insights More ❯

Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings into actionable insights More ❯

Pandas, NumPy and scikit-learn. Statistical & Machine Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings into actionable insights More ❯

foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series forecasting). Practical experience with Keras or PyTorch is required. Full-Stack Deployment: Demonstrable experience taking models to production, including building and deploying APIs with FastAPI and using Vertex AI for ML workflows. Visualization & Communication: Ability More ❯

with AI systems, machine learning models, or related technologies using Microsoft AI tools and Azure. Technical Skills Needed Familiarity with AI/ML frameworks and libraries (e.g., TensorFlow, PyTorch, Keras). Experience in Microsoft Azure as well as Microsoft AI tools (Copilot) is a must. Proficient in programming languages such as Python, Java, or C++. Understanding of system architecture and More ❯

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 … 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 More ❯

LLM features in a regulated environment with sensitive data. You’ll work with engineering to move models from idea to production. Tech Stack: Python, scikit-learn, PyTorch, TensorFlow/Keras, LangChain, Pydantic, Spark, Kafka, Databricks, MLflow, Azure, Docker, Kubernetes. Salary: Up to £100k Working Environment: Fully Remote in UK What you’ll do Research, prototype, and deploy LLM use cases … Q&A, summarisation, document processing) Build and tune models using scikit-learn, PyTorch, TensorFlow/Keras, and XGBoost Create data pipelines for batch and streaming with Spark and Kafka Use Databricks and MLflow for experiments, deployment, and monitoring What you’ll bring Hands-on Python for data science and ML Practical experience with LLM frameworks (e.g. LangChain) Familiar with Spark More ❯