1 to 25 of 64 Remote Kubeflow Jobs

work with clients and cross-functional teams. Preferred to Have: PhD in Computer Science, AI/ML, or related field. Experience with production ML systems and MLOps pipelines using Kubeflow or Vertex AI Pipelines. Knowledge of transformers and large language models (LLMs). Understanding of recommender systems, natural language processing, or graph-based search engines. Contributions to open-source ML More ❯

Address computer vision, NLP, and generative tasks using PyTorch, TensorFlow, or Transformer-based models. Model Deployment & MLOps Integrate CI/CD pipelines for ML models using platforms like MLflow, Kubeflow, or SageMaker Pipelines. Monitor model performance over time and manage retraining to mitigate drift. Business Insights & Decision Support Communicate analytical findings to key stakeholders in clear, actionable terms. Provide data … Python (NumPy, Pandas), R, SQL. ML/DL Frameworks: Scikit-learn, PyTorch, TensorFlow, Hugging Face Transformers. Big Data & Cloud: Databricks, Azure ML, AWS SageMaker, GCP Vertex AI. Automation: MLflow, Kubeflow, Weights & Biases for experiment tracking and deployment. Architectural Competencies Awareness of data pipelines, infrastructure scaling, and cloud-native AI architectures. Alignment of ML solutions with overall data governance and security More ❯

DevOps, cloud infrastructure, or site reliability engineering Strong expertise in multi-cloud and hybrid infrastructure including AWS, GCP, and on-premises environments Experience with MLOps tooling such as MLFlow, Kubeflow, DataRobot, or similar platforms for ML lifecycle management Experience with containerization and orchestration (Docker, Kubernetes) specifically for ML workloads and GPU clusters Deep understanding of CI/CD pipelines for More ❯

communication skills and a passion for mentoring and team leadership. Nice to Have Experience with data engineering tools (Airflow, Kafka, Spark). Knowledge of MLOps practices and tools (MLflow, Kubeflow). Contributions to open-source projects or AI research. Why Join? Work on impactful AI products used by global clients. Competitive salary, stock options, and flexible working hours. A collaborative More ❯

engineering techniques. Proficient in version control, CI/CD pipelines, and test-driven development. Nice to Have: Experience within financial services or fintech. Familiarity with MLOps tools (e.g., MLflow, Kubeflow, SageMaker). Understanding of regulatory or compliance frameworks. Academic background in mathematics, statistics, or quantitative disciplines. Who You Are: A natural problem-solver and independent thinker with a structured approach More ❯

engineering techniques. Proficient in version control, CI/CD pipelines, and test-driven development. Nice to Have: Experience within financial services or fintech. Familiarity with MLOps tools (e.g., MLflow, Kubeflow, SageMaker). Understanding of regulatory or compliance frameworks. Academic background in mathematics, statistics, or quantitative disciplines. Who You Are: A natural problem-solver and independent thinker with a structured approach More ❯

engineering techniques. Proficient in version control, CI/CD pipelines, and test-driven development. Nice to Have: Experience within financial services or fintech. Familiarity with MLOps tools (e.g., MLflow, Kubeflow, SageMaker). Understanding of regulatory or compliance frameworks. Academic background in mathematics, statistics, or quantitative disciplines. Who You Are: A natural problem-solver and independent thinker with a structured approach More ❯

engineering techniques. Proficient in version control, CI/CD pipelines, and test-driven development. Nice to Have: Experience within financial services or fintech. Familiarity with MLOps tools (e.g., MLflow, Kubeflow, SageMaker). Understanding of regulatory or compliance frameworks. Academic background in mathematics, statistics, or quantitative disciplines. Who You Are: A natural problem-solver and independent thinker with a structured approach More ❯

engineering techniques. Proficient in version control, CI/CD pipelines, and test-driven development. Nice to Have: Experience within financial services or fintech. Familiarity with MLOps tools (e.g., MLflow, Kubeflow, SageMaker). Understanding of regulatory or compliance frameworks. Academic background in mathematics, statistics, or quantitative disciplines. Who You Are: A natural problem-solver and independent thinker with a structured approach More ❯

engineering techniques. Proficient in version control, CI/CD pipelines, and test-driven development. Nice to Have: Experience within financial services or fintech. Familiarity with MLOps tools (e.g., MLflow, Kubeflow, SageMaker). Understanding of regulatory or compliance frameworks. Academic background in mathematics, statistics, or quantitative disciplines. Who You Are: A natural problem-solver and independent thinker with a structured approach More ❯

categories: experiment tracking and model metadata management (e.g. MLflow) orchestration of ML workflows (e.g. Metaflow) data and pipeline versioning (e.g. Data Version Control) model deployment, serving and monitoring (e.g. Kubeflow) Expert knowledge of automated artefact deployment using YAML based CI/CD pipelines and Terraform Working knowledge of one or more ML engineering frameworks (e.g. TensorFlow, PyTorch, Keras, Scikit-Learn More ❯

latest open source capabilities on public and private cloud infrastructure, Linux and Kubernetes. Our team applies expert insights to real-world customer problems, enabling the enterprise adoption of Ubuntu, Kubeflow, MLFlow, Feast, DVC and related analytics, machine learning and data technologies. We are working to create the world's best open source data platform, covering traditional SQL databases and today … to develop Kubernetes operators and Linux open source infrastructure-as-code. Work across the entire Linux stack, from kernel, networking, storage, to applications Architect cloud infrastructure solutions like Kubernetes, Kubeflow, OpenStack, and Spark Deliver solutions either on-premise or in public cloud (AWS, Azure, Google Cloud) Collect customer business requirements and advise them on Ubuntu and relevant open source applications More ❯

latest open source capabilities on public and private cloud infrastructure, Linux and Kubernetes. Our team applies expert insights to real-world customer problems, enabling the enterprise adoption of Ubuntu, Kubeflow, MLFlow, Feast, DVC and related analytics, machine learning and data technologies. We are working to create the world's best open source data platform, covering traditional SQL databases and today … to develop Kubernetes operators and Linux open source infrastructure-as-code. Work across the entire Linux stack, from kernel, networking, storage, to applications, Architect cloud infrastructure solutions like Kubernetes, Kubeflow, OpenStack and Spark, Deliver solutions either on-premise or in public cloud (AWS, Azure, Google Cloud), Collect customer business requirements and advise them on Ubuntu and relevant open source applications More ❯

systems (e.g., autonomous agents, tool usage frameworks, multi-step reasoning models). Able to implement large language models. Familiarity with MLOps (Machine Learning Operations) platforms: MLflow, Snowpark or ML Kubeflow and experience deploying models into production (e.g., REST APIs via Flask or FastAPI). Certifications in Snowflake, Databricks AWS or Azure. Prior experience working in regulated industries (e.g., defense, healthcare More ❯

and cloud deployment for large-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 on the development, training, and More ❯

systems. Key Responsibilities Build model lifecycle tooling (deployment, monitoring and alerting) for our predictive models (for example claims cost, conversion, retention, market models) Maintain and improve the development environment (Kubeflow) used by our Data Scientists and Actuaries Develop and maintain pricing analytics tools that enable faster impact assessments, reducing manual work Collaborate with the technical pricing, street pricing and product More ❯

between cloud-based systems using APIs Experience developing with containerisation (e.g Docker) and orchestration Kubernetes in cloud computing environments Familiarity with one or more data-oriented workflow orchestration frameworks (KubeFlow, Airflow, Argo, etc.) Ability to translate business needs to technical requirements Strong understanding of software testing, benchmarking, and continuous integration Exposure to machine learning methodology and best practices Preferred but More ❯

LangChain, Hugging Face Transformers, PyTorch, TensorFlow, Scikit-learn Agentic AI Tools: OpenAI GPT models, Crew,AI, Cohere, Pinecone (for vector databases), AutoGPT Data Engineering & ML Pipelines: Apache Airflow, MLflow, Kubeflow, dbt, Prefect Cloud & Deployment Platforms: AWS SageMaker, Azure ML, Google Vertex AI APIs & Orchestration: OpenAI API, Anthropic Claude, Weaviate, FastAPI (for AI applications) MLOps & Experimentation: Weights & Biases, DVC (Data Version More ❯

and cloud deployment for large-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 on the development, training, and More ❯

DevOps, cloud infrastructure, or site reliability engineering. Strong expertise in multi-cloud and hybrid infrastructure including AWS, GCP, and on-premises environments. Experience with MLOps tooling such as MLFlow, Kubeflow, DataRobot, or similar platforms for ML lifecycle management. Experience with containerization and orchestration (Docker, Kubernetes) specifically for ML workloads and GPU clusters. Deep understanding of CI/CD pipelines for More ❯

in‐office in Euston 2–3 days per week (right to work in the UK required). Nice‐to‐haves Clinical or health‐tech domain knowledge. MLOps tooling (MLflow, Kubeflow, Vertex Pipelines). Benefits Competitive salary and attractive equity in a high growth startup 25 days holiday + UK bank holidays. Flexible hours & focus on sustainable pace. Bright office minutes More ❯

in‐office in Euston 2–3 days per week (right to work in the UK required). Nice‐to‐haves Clinical or health‐tech domain knowledge. MLOps tooling (MLflow, Kubeflow, Vertex Pipelines). Benefits Competitive salary and attractive equity in a high growth startup 25 days holiday + UK bank holidays. Flexible hours & focus on sustainable pace. Bright office minutes More ❯

work in‐office in Euston 2–3days per week (right to work in the UK required). Nice‐to‐haves Clinical or health‐tech domain knowledge. MLOps tooling (MLflow, Kubeflow, Vertex Pipelines). Benefits Competitive salary and attractive equity in a high growth startup 25 days holiday +UK bank holidays. Flexible hours & focus on sustainable pace. Bright office minutes from More ❯

convert customer requirements or business challenges into well-defined machine learning solutions We are using many technologies day to day such as various AWS services, GCP, Kubernetes, Ray Serve, Kubeflow, and ReTool. Any experience in these areas would be a bonus Sprout.ai Values Hungry for Growth - Unleash your inner Sprout: Sprouts embrace growth, forget comfort zones, and help Sprout.ai thrive. More ❯

convert customer requirements or business challenges into well-defined machine learning solutions We are using many technologies day to day such as various AWS services, GCP, Kubernetes, Ray Serve, Kubeflow, and ReTool. Any experience in these areas would be a bonus Sprout.ai Values Hungry for Growth - Unleash your inner Sprout: Sprouts embrace growth, forget comfort zones, and help Sprout.ai thrive. More ❯