751 to 775 of 1,204 Containerisation Jobs

collaborating with teams to design, build, and maintain software Strong experience working in Agile environments , delivering MVPs in fortnightly sprints Hands-on experience with containerisation technologies Experience producing technical documentation throughout the SDLC Experience working with and enhancing existing codebases Proven ability to improve software resilience and stability Experience applying ...

such as Visio, Lucidchart, Draw.io Strong written communication skills and experience creating and reviewing technical documentation Experience of modern software development best practice eg containerisation, CI/CD Experience replacing legacy systems A technology and platform agnostic perspective Urgent requirement! Please apply by submitting your latest CV for immediate review ...

collaborating with teams to design, build, and maintain software Strong experience working in Agile environments , delivering MVPs in fortnightly sprints Hands-on experience with containerisation technologies Experience producing technical documentation throughout the SDLC Experience working with and enhancing existing codebases Proven ability to improve software resilience and stability Experience applying ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...

like TensorFlow, PyTorch, scikit-learn. Solid understanding of ML principles, algorithms, and their deployment in production. Experience with cloud platforms (AWS, GCP, Azure) and containerization (Docker/Kubernetes). Ability to work in highly regulated, security-conscious environments. Nice-to-Have: Experience in domains such as NLP, behaviour analytics, MLOps ...