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5 of 5 pydantic Jobs in Slough
slough, south east england, United Kingdom Generative Engineering
potential, and if you can apply properly, you’ve got an interview Knowledge of modern/larger-scale Python Experience in the FastAPI, Starlette, Pydantic suite (or similar) in Production Experience in at least one statically typed OOP language (Java/C++ etc) Some knowledge of Functional Programming (e.g. ML More ❯
slough, south east england, United Kingdom Fundment
technical and non-technical teams This role is 70% hands on, 30% management Technical Expertise Required - Python - proficiency with Pandas, Numpy, SQLAlchemy, FastAPI, and Pydantic MySQL, PostgreSQL, and Redis Hands-on experience with Google Cloud Platform (GCP) services like Pub/Sub, Cloud Run, VMs, Load Balancers, and Cloud Logging. More ❯
slough, south east england, United Kingdom
Hybrid / WFH Options WMtech
skills and a bias toward action. Technologies You’ll Work With Experience in some or most of the following: Languages/Frameworks: Python, FastAPI, Pydantic, Streamlit (for internal tools) AI: AgenticFlows, GenAI, LLMs, and multimodal systems Architecture: Microservices, RESTful APIs, async programming Infrastructure: Docker, Terraform, GitHub Actions, GCP (preferred) Datastores More ❯
slough, south east england, United Kingdom
Hybrid / WFH Options Prism Digital
role is based in London (Victoria), with hybrid working: three days in the office and two from home. Responsibilities: Python backend development using FastAPI, Pydantic, and related frameworks JavaScript (React) frontend development based on FIGMA designs KAFKA integration for building event-driven architectures Database development using CosmosDB and MongoDB Rapid More ❯
slough, south east england, United Kingdom Tangent International
or software engineering roles • Bachelor’s degree or equivalent in Computer Science, Data Science, or related technical field • Strong Python programming (especially pandas, GeoPandas, Pydantic, boto3) • Experience with geospatial data and data engineering for ML applications • Cloud proficiency (preferably AWS) and experience with containerized environments (Docker, EKS) • Solid Git practices … with cross-functional teams • Experience working with financial services or asset management domains preferred Technical Stack: Data Pipeline Stack: Python 3, pandas, GeoPandas, boto3, Pydantic, Data Version Control (DVC) 2 Core API Stack: Python 3, Django 4 Infrastructure: AWS, EKS, Docker, ADO (for CI/CD pipelines, git hosting, ticket More ❯
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