76 to 100 of 478 gRPC Jobs in England

of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services). Hands-on experience with cloud platforms (AWS, GCP, Azure) for model training and deployment. Deep understanding of MLOps concepts: monitoring, logging, CI/CD for More ❯

of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services). Hands-on experience with cloud platforms (AWS, GCP, Azure) for model training and deployment. Deep understanding of MLOps concepts: monitoring, logging, CI/CD for More ❯

of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services). Hands-on experience with cloud platforms (AWS, GCP, Azure) for model training and deployment. Deep understanding of MLOps concepts: monitoring, logging, CI/CD for More ❯

of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services). Hands-on experience with cloud platforms (AWS, GCP, Azure) for model training and deployment. Deep understanding of MLOps concepts: monitoring, logging, CI/CD for More ❯

of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services). Hands-on experience with cloud platforms (AWS, GCP, Azure) for model training and deployment. Deep understanding of MLOps concepts: monitoring, logging, CI/CD for More ❯

of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services). Hands-on experience with cloud platforms (AWS, GCP, Azure) for model training and deployment. Deep understanding of MLOps concepts: monitoring, logging, CI/CD for More ❯

of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services). Hands-on experience with cloud platforms (AWS, GCP, Azure) for model training and deployment. Deep understanding of MLOps concepts: monitoring, logging, CI/CD for More ❯

of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services). Hands-on experience with cloud platforms (AWS, GCP, Azure) for model training and deployment. Deep understanding of MLOps concepts: monitoring, logging, CI/CD for More ❯

of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services). Hands-on experience with cloud platforms (AWS, GCP, Azure) for model training and deployment. Deep understanding of MLOps concepts: monitoring, logging, CI/CD for More ❯

of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g., serving models with REST APIs, gRPC, or via cloud services). Hands-on experience with cloud platforms (AWS, GCP, Azure) for model training and deployment. Deep understanding of MLOps concepts: monitoring, logging, CI/CD for More ❯

The ideal candidate will have the following skills/experience: Go/Python/Java Cloud provider API integration (e.g. AWS, GCP, Azure) Communication protocols such as HTTP and gRPC Kubernetes hosted microservices Docker SQL You will have at least 8 years of professional software development experience and be eligible to work in the UK with either weekly or monthly More ❯

experience with event driven architecture and distributed messaging technologies ( Kafka ) Preferred qualifications, capabilities, and skills Hands on experience another statically compiled language like Golang, Rust or C++ Experience with gRPC and Google Protocol Buffers Experience with caching technologies, e.g. Redis Experience with infrastructure as code software, e.g. Terraform Experience using and designing schemas/data structures in resilient SQL and More ❯

degree in Computer Science (or related fields). Experience with AWS and Docker. Interest in AI, and familiarity with building LLM-based agents. Exposure to contract-first development (OpenAPI, gRPC/Protocol Buffers). Ability to design scalable and efficient system architectures. Ability to navigate rapidly changing priorities in a growing startup environment. [Optional] Previous experience working at a startup More ❯

of our core technologies: Python for our application code, APIs and SDK, and scripting SQL and NoSQL databases: PostgreSQL, Couchbase, DynamoDB Event-driven architecture, employing technologies such as Kafka, gRPC and Protobuf for event definitions Solver technology and algorithms to drive our workflow scheduling solver engine Deployment on AWS to IoT Greengrass, ECS, Lambda and EKS, with infrastructure managed via More ❯

end and back-end components Utilize your expertise in NoSQL DB (CosmosDB) to design, develop and optimize data models for seamless storage within a distributed system Create RESTFul APIs (gRPC) to enable smooth communication between microservices and external systems Conduct regular code reviews, unit testing, CI and maintain high code quality and reliability To be successful, we’re seeking interest More ❯

degree in Computer Science (or related fields). Experience with AWS and Docker. Interest in AI, and familiarity with building LLM-based agents. Exposure to contract-first development (OpenAPI, gRPC/Protocol Buffers). Ability to design scalable and efficient system architectures. Ability to navigate rapidly changing priorities in a growing startup environment. [Optional] Previous experience working at a startup More ❯

and what our environment looks like: Python for our application code, APIs and SDK SQL and NoSQL databases: PostgreSQL, Couchbase, DynamoDB Event-driven architecture, employing technologies such as Kafka, gRPC and Protobuf for event definitions Solver technology and algorithms to drive our workflow scheduling solver engine Deployment on AWS to IoT Greengrass, ECS, Lambda and EKS, with infrastructure managed via More ❯

Experience working with many stakeholders to review and agree on a complex system design. Hands-on experience with another statically compiled language (e.g., Golang, Rust, C++). Experience with gRPC and Google Protocol Buffers. Experience with caching technologies (e.g., Redis). Experience with infrastructure as code software (e.g., Terraform). Certified Kubernetes and public cloud knowledge (e.g., CKAD, AWS certifications More ❯

GitHub, DevOps tools, metrics/monitoring, ...) Proficiency in front-end technologies: JavaScript, Typescript, React.js, Angular.js or similar. API development using technologies and standards like REST/GraphQL/gRPC or similar. Experience in an open-source web framework preferably implemented in Python, Java, Scala, or similar. Experience with Authentication & Authorisation Mechanisms e.g OAuth2 Application experience of CI/CD More ❯

Backend Engineering Lead ( Rust & Pyhton, C++) Opportunity Overview: A leading technology-enabled advisory firm specialising in financial market risk management is seeking a skilled Back-End Engineering Team Lead. This is a fantastic opportunity to play a key role in More ❯

Backend Engineering Lead ( Rust & Pyhton, C++) Opportunity Overview: A leading technology-enabled advisory firm specialising in financial market risk management is seeking a skilled Back-End Engineering Team Lead. This is a fantastic opportunity to play a key role in More ❯

Backend Engineering Lead ( Rust & Pyhton, C++) Opportunity Overview: A leading technology-enabled advisory firm specialising in financial market risk management is seeking a skilled Back-End Engineering Team Lead. This is a fantastic opportunity to play a key role in More ❯

Backend Engineering Lead ( Rust & Pyhton, C++) Opportunity Overview: A leading technology-enabled advisory firm specialising in financial market risk management is seeking a skilled Back-End Engineering Team Lead. This is a fantastic opportunity to play a key role in More ❯

or similar, CI/CD including GIT repositories and pipelines. Software testing expertise Write clean, readable, and reusable code with appropriate technologies Knowledge of HTTP, REST, Web Sockets and gRPC Beneficial requirements: Analytical tools such as Excel, PowerBI, Tableau Python analytical libraries e.g. Plotly, Numpy Socket programming Person specification Background in computer science, finance, maths or other quantitative subject Hands More ❯

your tool kit we will need to see experience of most of the following: Python (FastAPI, Numpy, Scipy, Matplotlib, PyQt/PySide, etc) TypeScript, React, Chakra UI REST, GraphQL, gRPC, Socket.IO SQL, Django, GitLab, Continuous Integration & Delivery, Docker, Kubernetes VTK A great time to join this client as they embark on a new era. A lot of investment in both More ❯