4 of 4 Permanent Apache Spark Jobs in Bath

LLMs), and specialized models in Computer Vision and NLP. Big Data Engineering: Design, build, and optimize high-throughput, distributed data pipelines and features using Apache Spark (Scala) and Hive on massive datasets to support model training and inference. Cross-Cloud Execution: Lead the design and deployment … environment. Required Skills and Expertise (10+ Years) 1. Big Data and Cloud Mastery Programming & Big Data: 10+ years of extensive, hands-on experience with Apache Spark, with strong preference for production development using Scala. Deep expertise with Apache Hive for data querying and management. Cloud Proficiency: Demonstrated ...

models into production environments. Data & Engineering Skills Strong SQL skills and experience working with large datasets. Familiarity with data processing tools (Pandas, NumPy, Spark). Experience building APIs (FastAPI, Flask) for ML services. ...

looking for an experienced Senior Data Engineer to assist with building and managing data pipelines using the Elastic Stack (Elasticsearch, Logstash, Kibana) and Apache NiFi Key Responsibilities: Design, develop, and maintain secure and scalable data pipelines using the Elastic Stack (Elasticsearch, Logstash, Kibana) and Apache NiFi. Implement data … Skillset: Experience working in government, defence, or highly regulated industries with knowledge of relevant standards. Experience with additional data processing and ETL tools like Apache Kafka, Spark, or Hadoop Familiarity with containerization and orchestration tools such as Docker and Kubernetes. Experience with monitoring and alerting tools such ...

data. You'll work with engineering to move models from idea to production. Tech Stack: Python, scikit-learn, PyTorch, TensorFlow/Keras, LangChain, Pydantic, Spark, Kafka, Databricks, MLflow, Azure, Docker, Kubernetes. Salary: Up to £100k Working Environment: Fully Remote in UK What you'll do Research, prototype, and deploy … summarisation, document processing) Build and tune models using scikit-learn, PyTorch, TensorFlow/Keras, and XGBoost Create data pipelines for batch and streaming with Spark and Kafka Use Databricks and MLflow for experiments, deployment, and monitoring What you'll bring Hands-on Python for data science and ML Practical ...