6 of 6 DemandTrendPermanent Apache Spark Jobs in Surrey

AWS, Azure) and containerisation (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, SageMaker, Airflow). Experience working with large-scale datasets and distributed computing frameworks (e.g., Spark). Strong communication skills and ability to work collaboratively in a team environment. MSc or PhD in Computer Science, Engineering, Mathematics, or a related field. Desirable Skills Experience with More ❯

AWS, Azure) and containerisation (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, SageMaker, Airflow). Experience working with large-scale datasets and distributed computing frameworks (e.g., Spark). Strong communication skills and ability to work collaboratively in a team environment. MSc or PhD in Computer Science, Engineering, Mathematics, or a related field. Desirable Skills Experience with More ❯

exposure to cloud-native data infrastructures (Databricks, Snowflake) especially in AWS environments is a plus Experience in building and maintaining batch and streaming data pipelines using Kafka, Airflow, or Spark Familiarity with governance frameworks, access controls (RBAC), and implementation of pseudonymisation and retention policies Exposure to enabling GenAI and ML workloads by preparing model-ready and vector-optimised datasets More ❯

AWS, Azure) and containerisation (Docker, Kubernetes). Familiarity with MLOps practices and tools (e.g., MLflow, SageMaker, Airflow). Experience working with large-scale datasets and distributed computing frameworks (e.g., Spark). Strong communication skills and ability to work collaboratively in a team environment. MSc or PhD in Computer Science, Engineering, Mathematics, or a related field. Desirable Skills Experience with More ❯

version control, e.g., Git. Knowledge of OO programming, software design, i.e., SOLID principles, and testing practices. Knowledge and working experience of AGILE methodologies. Proficient with SQL. Familiarity with Databricks, Spark, geospatial data/modelling Exposure to MLOps, model monitoring principles, CI/CD and associated tech, e.g., Docker, MLflow, k8s, FastAPI etc. are a plus. Additional Information What’s More ❯

solutions from structured and unstructured data. Build data pipelines, models, and AI applications, using cloud platforms and frameworks such as Azure AI/ML Studio, AWS Bedrock, GCP Vertex, Spark, TensorFlow, PyTorch, etc. Build and deploy production grade fine-tuned LLMs and complex RAG architectures. Create and manage the complex and robust prompts across the GenAI solutions. Communicate effectively More ❯