1 to 25 of 40 MLflow Jobs in the UK

pandas, scikit-learn, Jupyter etc., and version control, e.g., Git. Exposure to LLMOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc. Knowledge of Langchain, huggingface and LLM offerings by 3rd party vendors. Knowledge of OO programming and software design, i.e., SOLID principles. Knowledge ...

learning and improvement. Your Profile Essential Skills/Knowledge/Experience Knowledge of machine learning frameworks (e.g., PySpark, PyTorch) and model deployment tools (e.g., MLflow, TensorFlow Serving). Strong experience with data processing frameworks (e.g., Apache Spark, Flink). Expertise in SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra ...

learning and improvement. Your Profile Essential skills/knowledge/experience: Knowledge of machine learning frameworks (e.g., PySpark, PyTorch) and model deployment tools (e.g., MLflow, TensorFlow Serving). Strong experience with data processing frameworks (e.g., Apache Spark, Flink). Expertise in SQL and NoSQL databases (e.g., MySQL, PostgreSQL, MongoDB, Cassandra ...

Have Experience with marketplace or matching algorithms. Exposure to flexibility markets, virtual power plants, or reconciliation/settlement processes. Experience with ML deployment frameworks (MLflow, Vertex AI, SageMaker). Knowledge of optimisation libraries such as Gurobi, OR‐Tools, or Pyomo. ...

degree in Computer Science, Machine Learning, Engineering , or a closely related discipline. Bonus Points Experience with MLOps and model serving platforms such as BentoML, MLflow, or SageMaker . Hands-on work with streaming and batch data pipelines using tools like Spark, Airflow, or Apache Beam . Background in front ...

stack (pandas, scikit-learn, Jupyter, etc.) and version control tools like Git. Exposure to LLMOps, model monitoring, CI/CD and related technologies (Docker, MLflow, Kubernetes, FastAPI, etc.). Knowledge and working experience of AGILE methodologies. At Ageas we offer a wide range of benefits to support you and your ...

lifecycle management Lead documentation, knowledge transfer, and mentoring to upskill internal teams Technical requirements Strong Python and ML frameworks (PyTorch, TensorFlow) MLOps tooling (MLflow, Kubeflow or similar) Databricks Docker, Kubernetes, CI/CD pipelines Cloud platforms (AWS, Azure or GCP); Terraform experience preferred Financial services experience highly desirable A hands ...

Azure) and containerisation (Docker, Kubernetes) Solid understanding of ML fundamentals (model training, evaluation, common architectures) Desired Skills (Bonus Points) Experience with MLOps tooling (MLflow, Kubeflow, Weights & Biases, or similar) Building data pipelines (real-time or batch) using tools like Apache Spark, Kafka, Airflow, or dbt Familiarity with recommender systems, transformers ...

Face Solid understanding of machine learning fundamentals and performance evaluation techniques Experience working in cloud platforms (AWS, GCP, or Azure) with MLOps tools (e.g. MLflow, SageMaker, Vertex AI) Comfortable working independently and delivering high-quality work to tight timelines Experience working in fast-paced environments or scale-up settings Company ...

pandas, scikit-learn, Jupyter, etc.) and version control tools like Git. Any exposure to LLMOps, model monitoring, CI/CD and related technologies (Docker, MLflow, Kubernetes, FastAPI, etc.). At Ageas we offer a wide range of benefits to support you and your family inside and outside of work, which ...

scikit-learn Eagerness to learn, curiosity, and a problem-solving mindset Nice to Have Cloud experience (AWS, GCP, Azure) Familiarity with MLOps tools (Docker, MLflow, Kubeflow) Deep learning knowledge (CNNs, RNNs, Transformers) Internship, research, or academic projects in ML/AI Why Join Hands-on experience with cutting-edge ...

data science or a closely related field. Nice to Have Skills * Experience with Databricks for data engineering or ML workflows. * Familiarity with Azure ML, MLflow, or similar MLOps tooling. * Exposure to feature engineering best practices and model lifecycle management. Soft Skills * Strong communication skills with the ability to explain complex ...

Data Scientist: Experience with deep learning frameworks advanced modelling techniques Familiarity with MLOps concepts model monitoring deployment pipelines Exposure to tools such as Databricks MLflow feature stores Experience working in Agile product-led delivery environments Understanding of data governance ethics model explainability Relevant professional certifications relating to cloud data platforms ...

evaluation frameworks, and simulators . 2. MLOps, Quality & Productionisation Design and implement robust CI/CD and MLOps pipelines using platforms such as Databricks, MLflow, Unity Catalog, Snowflake, and Azure ML. Establish model observability across performance, drift, cost controls, and operational reliability . Apply AIOps practices to enable automated retraining … inputs, claims triage, and bordereaux . Ability to design AI solutions aligned to insurance performance and profitability metrics . Technical Environment Model Lifecycle & Governance MLflow, Databricks Model Serving, Unity Catalog Feature stores (Databricks Feature Store, Feast) Model monitoring and governance platforms Data Engineering Databricks Lakehouse, Spark Kafka/Confluent Delta ...

members Skillset: Strong Python and ML libraries (scikit-learn, PyTorch, pandas, NumPy) Experience with AWS cloud services (SageMaker, Lambda, S3) Familiarity with MLOps tools (MLflow, Weights & Biases) Knowledge of NLP, computer vision, or time-series analysis Ability to design experiments and apply statistical validation Understanding of Responsible AI principles ...

such as Amazon SageMaker . Comfortable with software version control (Git) and collaborative workflows. Experience with experiment tracking/management tools (e.g., SageMaker Studio , MLflow, Weights & Biases). Machine Learning Expertise Proven ability to build, test, and validate hypotheses through well-designed ML experiments. Hands-on experience creating and deploying ...

DataBricks, Snowflake, etc.)* Advanced degree or certification in ML, NLP, or a related field* Knowledge of DevOps tooling and best practices* Experience with MLFlow, Weights & Biases, or similar experimentation frameworks* Strong stakeholder or customer-facing communication skills* Demonstrated impact of your models on business or research outcomes Job Offer Competitive ...

visualization tools such as Power BI, integrated with Databricks SQL endpoints for interactive reporting and dashboards. Strong understanding of statistical methods and ML frameworks (MLflow, scikit-learn, TensorFlow) for predictive modelling, experiment tracking, and deployment within Databricks. Project Delivery Experience 7+ years of experience with Microsoft data technologies. 8+ years ...

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 extraordinary ...

Hugging Face ecosystem Experience with audio or speech models and frameworks. Experience building and maintaining end-to-end ML pipelines and MLOps tooling (e.g. MLflow, Weights & Biases, DVC, or similar). Strong Python skills; experience with Docker, CI/CD, and cloud platforms (Azure preferred) Practical experience designing agentic ...

Hugging Face ecosystem Experience with audio or speech models and frameworks. Experience building and maintaining end-to-end ML pipelines and MLOps tooling (e.g. MLflow, Weights & Biases, DVC, or similar). Strong Python skills; experience with Docker, CI/CD, and cloud platforms (Azure preferred) Practical experience designing agentic ...

working knowledge of: Cloud infrastructure, including Kubernetes, OpenStack, Docker, microservices, and public cloud services (AWS, GCP, Azure) AI/ML infrastructure tools (e.g., Kubeflow, MLflow, NVIDIA AI), and how they integrate with cloud-native platforms DevOps and automation tools, including CI/CD pipelines Observability tooling, including open-source monitoring ...

working knowledge of: Cloud infrastructure, including Kubernetes, OpenStack, Docker, microservices, and public cloud services (AWS, GCP, Azure) AI/ML infrastructure tools (e.g., Kubeflow, MLflow, NVIDIA AI), and how they integrate with cloud-native platforms DevOps and automation tools, including CI/CD pipelines Observability tooling, including open-source monitoring ...

working knowledge of: Cloud infrastructure, including Kubernetes, OpenStack, Docker, microservices, and public cloud services (AWS, GCP, Azure) AI/ML infrastructure tools (e.g., Kubeflow, MLflow, NVIDIA AI), and how they integrate with cloud-native platforms DevOps and automation tools, including CI/CD pipelines Observability tooling, including open-source monitoring ...

working knowledge of: Cloud infrastructure, including Kubernetes, OpenStack, Docker, microservices, and public cloud services (AWS, GCP, Azure) AI/ML infrastructure tools (e.g., Kubeflow, MLflow, NVIDIA AI), and how they integrate with cloud-native platforms DevOps and automation tools, including CI/CD pipelines Observability tooling, including open-source monitoring ...