12 of 12 Permanent Amazon SageMaker Jobs in London

orchestration tools like Kubeflow, Airflow, or Metaflow. Cloud Architecture: Expertise in deploying ML workloads on AWS, GCP, or Azure, utilizing managed services like SageMaker or Vertex AI. Data Foundations: Strong understanding of data modeling, feature stores, and distributed computing (e.g., Spark, Dask). Qualifications & Experience Experience: 5+ years ...

engineers What We're Looking For: Proficiency in Python and ML frameworks (scikit-learn, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda) Familiarity with containerisation (Docker) and orchestration (Kubernetes/ECS) Knowledge of LLMOps and GenAI tools (LangChain, LangSmith) Understanding of feature engineering and vector databases ...

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. ...

automated testing (unit, integration, end-to-end) Ability to communicate complex technical concepts to non-technical stakeholders Nice to Have Experience with MLflow, DVC, SageMaker Workflow orchestration tools (Dagster/Airflow) Containerisation (Docker, ECS) Domain experience in transportation, airlines, operations, or network optimisation Qualifications Master’s degree in Data ...

expert should have: A strong academic background in data science, computer science, mathematics, or a related field. Hands-on experience with AWS ML stack (SageMaker, Lambda, Redshift). Proven ability to design and implement machine learning algorithms and models. Proficiency in Python, SQL, and ML libraries (e.g., scikit-learn ...

technical stakeholders Mentor junior team 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 ...

e.g. seaborn) Proficient in working with cloud platforms (AWS preferred), code versioning (Git), experiment tracking (e.g. MLflow) Experience with cloud-based ML tools (e.g. SageMaker), data and model versioning (e.g. DVC), CI/CD (e.g. GitHub Actions), workflow orchestration (e.g. Airflow/Dagster) and containerised solutions (e.g. Docker ...

similar large-scale ranking models. Generative AI & Technical Proficiency: Hands-on experience with LLM fine-tuning, Python, modern NLP frameworks, and familiarity with AWS SageMaker, Docker, and Airflow. Strong mathematical and statistical foundation. Ethical Drive: Commitment to ethical and fair AI practices that ensureequitableoutcomes for all users. Additional Information ...

Evidence of defining, building and maintaining infrastructure as code using Terraform. Experience of creating cloud-based solutions - specifically AWS, utilising the likes of Athena, Sagemaker and Glue, as well as associated cloud services. You and your role As our Technical lead, you will lead multi-disciplinary teams ...

machine learning solutions Strong skills in Python, SQL, and ML libraries (e.g. scikit-learn, XGBoost, PyTorch, TensorFlow) Hands-on experience with AWS ML services (SageMaker, Lambda, Redshift) Ability to clearly communicate insights to non-technical stakeholders Strong analytical thinking, collaboration skills, and a results-driven mindset Role responsibilities: Build … tune, and maintain predictive and ML models using AWS SageMaker Analyse large datasets and perform feature engineering to improve model performance Run experiments, test hypotheses, and optimise models for accuracy and value Monitor model performance and manage retraining over time Collaborate with Data Engineers, BI Developers, and Analysts ...

runtime environments. Work closely with data engineering, platform engineering, security, MLOps, and Independent Model Monitoring (IMM) teams. Contribute to integration efforts with AWS SageMaker, model pipelines, and enterprise data platforms. Use technologies such as AWS, SageMaker, Python, Java, Kafka, Open Telemetry, and cloud-native monitoring stacks. Support governance … data platforms. Proficiency in Python, SQL, Java , and modern data processing frameworks. Experience working with cloud-based AI/ML ecosystems , particularly AWS SageMaker (required). Understanding of monitoring frameworks , observability pipelines, and dashboards. Familiarity of event-driven architectures and messaging systems (Kafka, Vert.x, or similar). Knowledge ...

Data Scientist Hybrid Working – Local Site – 1-2 days a week on site. Financial Services Lorien's leading banking client is looking for a number of Data Scientists to join them on a new long ...