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 ❯
Grantham, England, United Kingdom Hybrid / WFH Options
Bending Spoons
your responsibilities Master your toolkit. By working across diverse tech stacks, you’ll refine your ability to choose the right tools for every challenge. From monolithic to microservices architectures, gRPC to REST APIs, Kubernetes to Docker, Python to Rust—you’ll show that true expertise isn’t about using the trendiest technologies, but about understanding their purpose to unleash their More ❯
Nottingham, Nottinghamshire, United Kingdom Hybrid / WFH Options
Bending Spoons
your responsibilities Master your toolkit. By working across diverse tech stacks, you'll refine your ability to choose the right tools for every challenge. From monolithic to microservices architectures, gRPC to REST APIs, Kubernetes to Docker, Python to Rust-you'll show that true expertise isn't about using the trendiest technologies, but about understanding their purpose to unleash their More ❯
Nottingham, England, United Kingdom Hybrid / WFH Options
Bending Spoons
your responsibilities Master your toolkit. By working across diverse tech stacks, you’ll refine your ability to choose the right tools for every challenge. From monolithic to microservices architectures, gRPC to REST APIs, Kubernetes to Docker, Python to Rust—you’ll show that true expertise isn’t about using the trendiest technologies, but about understanding their purpose to unleash their More ❯
