1 to 25 of 32 Kubeflow Jobs in the UK

standard software engineering methodology, e.g. unit testing, test automation, continuous integration, code reviews, design documentation Working experience with native ML orchestration systems such as Kubeflow, Step Functions, MLflow, Airflow, TFX... Relevant working experience with Docker and Kubernetes is a big plus More ❯

Python, experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI). What we offer Culture of caring: At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every More ❯

Python, experience with AI/ML frameworks (e.g., TensorFlow, PyTorch), and experience with MLOps frameworks/tools (e.g. Sagemaker pipelines, Azure ML Studio, VertexAI, Kubeflow, MLFlow, Seldon, EvidentlyAI). What We Offer Culture of Caring: At GlobalLogic, we prioritize a culture of caring. Across every region and department, at every More ❯

platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Hands-on experience with CI/CD pipelines, version control, and ML workflows (MLflow, Kubeflow). Proven track record of delivering ML models that solve real-world business challenges at scale. Excellent communication skills with the ability to work effectively More ❯

platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Hands-on experience with CI/CD pipelines, version control, and ML workflows (MLflow, Kubeflow). Proven track record of delivering ML models that solve real-world business challenges at scale. Excellent communication skills with the ability to work effectively More ❯

and training across GPUs and cloud-based architectures. Ensure security and compliance for ML platforms handling sensitive data. Evaluate and integrate MLOps tools (MLflow, Kubeflow, etc.) to enhance efficiency. Implement monitoring and alerting systems to detect anomalies and maintain model reliability. What We’re Looking For 3+ years of experience More ❯

and training across GPUs and cloud-based architectures. Ensure security and compliance for ML platforms handling sensitive data. Evaluate and integrate MLOps tools (MLflow, Kubeflow, etc.) to enhance efficiency. Implement monitoring and alerting systems to detect anomalies and maintain model reliability. What We’re Looking For 3+ years of experience More ❯

in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or email me at mmatysik@trg-uk.com. More ❯

in Python, including PyTorch, Hugging Face Transformers, Pandas, and scikit-learn. Strong understanding of cloud services (preferably AWS) and experience with Docker, Kubernetes, MLFlow, Kubeflow, or similar MLOps tools. 📩 Interested? Apply below or email me at mmatysik@trg-uk.com. More ❯

to support machine learning models. Preferred Qualifications: AWS Certified Machine Learning - Specialty or other relevant certifications. Experience with machine learning deployment frameworks (TensorFlow Serving, Kubeflow, MLflow) and managing containerized workloads with ECS/EKS. Deep understanding of data privacy regulations, model security, and designing solutions that are compliant with industry More ❯

Ability to communicate complex ideas in machine learning to non-technical stakeholders. You may have: Experience with one or more ML Ops frameworks - MLFlow, Kubeflow, Azure ML, Sagemaker. Strong theoretical foundations in linear algebra, probability theory, or optimization. Experience and training in finance and operations domains. Deep experience with ML More ❯

making processes Hands-on experience with AI/ML frameworks (TensorFlow, PyTorch), LLM orchestration tools (LangChain, LangGraph), MLOps practices and tooling (such as MLflow, Kubeflow, or similar), vector databases, and cloud platforms (AWS, Azure, GCP) with their AI/ML offerings Preferably hands-on experience with voice technologies and computer More ❯

to manage cloud infrastructure to ensure high availability, scalability, and cost efficiency. Nice-to-Have · Experience with ML orchestration platforms like MLflow, SageMaker Pipelines, Kubeflow, or similar. · Familiarity with model quantization, pruning, or other performance optimization techniques. · Exposure to distributed training frameworks like Unsloth, DeepSpeed, Accelerate, or FSDP. More ❯

drive to learn new technologies and techniques. Experience/aptitude towards research and openness to learn new technologies. Experience with Azure, Spark (PySpark), and Kubeflow - desirable. We pay competitive salaries based on experience of the candidates. Along with this, you will be entitled to an award-winning range of benefits More ❯

NeurIPS, ICML, EMNLP, CVPR, etc.) and/or journals Strong high-level programming skills (e.g., Python), frameworks and tools such as DeepSpeed, Pytorch lightning, kubeflow, TensorFlow, etc. Strong written and verbal communication skills to operate in a cross functional team environment More ❯

SOC 2). Collaborate with ML/AI Teams Package and deploy large‑language‑model (LLM) training jobs on distributed GPU clusters (Slurm, Ray, Kubeflow, or AWS SageMaker). Optimize model‑serving (Triton, vLLM, TorchServe) for low‑latency, high‑throughput inference. Cost & Performance Optimization Track cloud spend, right‑size resources More ❯

Experience in the following would be beneficial: Experience implementing model governance e.g. model versioning, drift reporting etc. Experience with MLOps tools such as MLFlow, Kubeflow, or DVC. Experience with distributed processing systems like Spark (Scala and PySpark would be invaluable). Experience with LLMs, and/or RAG architecture. Experience More ❯

Kernel, and tools such as MS tooling, Co-Pilot Studio, ML Studio, Prompt flow, Kedro, etc. Proficiency with pipeline orchestration tools, such as Airflow, Kubeflow, and Argo. Outstanding communication skills, combining subject matter expertise with a flair for statistics. A results-driven attitude, a passion for innovation, and a self More ❯

for Natural Language Processing and Computer Vision Strong grasp of basic probability concepts and machine learning lifecycle Experience with workflow and pipelining frameworks (e.g., Kubeflow, MLFlow, Argo) Understanding and application of Ethical AI considerations Ready to take your career to the next level? Apply today and be part of something More ❯

scale models. Solid programming skills in Python and familiarity with machine learning frameworks like TensorFlow, PyTorch, Hugging Face Transformers, and MLOps tools (e.g., MLflow, Kubeflow). Strong analytical and problem-solving skills, with an aptitude for translating complex theoretical research into practical applications. Day to Day Conduct research and implementation More ❯

programming proficiency in Python, with additional experience in C/C++ for performance-sensitive applications. • Tooling Knowledge: Proficiency in MLOps frameworks such as MLflow, Kubeflow, or SageMaker Pipelines; familiarity with Docker and Kubernetes. • Optimization Techniques: Hands-on experience with model performance optimization techniques and distributed training frameworks (e.g., DeepSpeed, FSDP More ❯

with Azure/GCP and AWS. Experience in automation of performance testing. Data environments exposure is a plus (Airflow, EMR, SageMaker, Ray, Tensorflow, MLflow, Kubeflow, Dask). Working conditions: Occasional out of hour's conferencing with overseas colleagues. Occasional out of hours or weekend work. A workplace that supports & role More ❯

life cycle to enable the building and maintenance of our AI systems. Our teams make extensive use of open source technologies such as Kubernetes, Kubeflow, KServe, Argo, Buildpacks, and other cloud-native MLOps technologies. From technical governance to upstream collaboration, we are committed to enhancing the impact and sustainability of More ❯

life cycle to enable the building and maintenance of our AI systems. Our teams make extensive use of open source technologies such as Kubernetes, Kubeflow, KServe, Argo, Buildpacks, and other cloud-native MLOps technologies. From technical governance to upstream collaboration, we are committed to enhancing the impact and sustainability of More ❯

Tadaweb is a pioneering technology company with roots in Luxembourg and a growing global presence, with offices in the United Kingdom, France, and the United States. For over 13 years, we’ve been on a mission to make the world More ❯