51 to 66 of 66 Apache Spark Jobs in London

PyTorch) into real customer value Working closely with engineering teams using TypeScript, Node.js, React, and Next.js Partnering with data teams working across AWS, Kafka, Spark, and modern data pipelines Shaping products built on secure, scalable fintech architecture (Event-driven, microservices, serverless) Running discovery experiments and validating concepts at speed ...

Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics ...

Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics ...

Deep expertise in search and recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics ...

Aker Systems was founded in 2017 by a team of experienced technology professionals who recognised an opportunity to provide highly secure enterprise data platforms to large organisations. We build and operate ground-breaking, ultra-secure ...

Feast, AWS Feature Store) Experience with containerisation (Docker) and orchestration (Kubernetes, ECS) Familiarity with Infrastructure as Code (Terraform, CloudFormation) Experience with data processing frameworks (Spark, Dask) for large-scale workloads Understanding of data governance and compliance frameworks ...

models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. ...

models for performance, scalability, and accuracy. Qualifications: Deep knowledge of neural networks (CNNs, RNNs, LSTMs, Transformers). Strong experience with data tools (Pandas, NumPy, Apache Spark). Solid understanding of NLP algorithms. Experience integrating ML models via RESTful APIs. Familiarity with CI/CD pipelines and deployment automation. ...

lead embedded data science teams, partnering effectively with senior stakeholders across multiple domains Hands-on technical expertise with tools such as Databricks, Python, Spark, and GCP/BigQuery Engineering mindset, with experience moving teams toward machine learning engineering best practice Credibility to lead long-tenured individual contributors while providing ...

tooling and working with large transactional datasets Understanding of OTC products including CDS, Interest Rate Swaps and Variance Swaps Highly Desirable Experience with C++, Spark, Kafka or other distributed compute tools Exposure to position keeping, risk, or PnL systems Strong debugging, profiling and optimisation capability across data pipelines ...

Level grades are included on your CV). Basic scripting knowledge in Python or Bash Excellent customer-facing skills You have a sales spark - while this role isn't a focussed sales role, this is required due to the nature of the role A motivated self-starter with ...

power, and deep knowledge of just about every industry. We believe a mix of data, analytics, automation, and responsible AI can do almost anything—spark digital metamorphoses, widen the range of what humans can do, and breathe life into smart products and services. Want to join our crew ...

power, and deep knowledge of just about every industry. We believe a mix of data, analytics, automation, and responsible AI can do almost anything—spark digital metamorphoses, widen the range of what humans can do, and breathe life into smart products and services. Want to join our crew ...

fast-paced, challenging environment. Key Responsibilities: Design, implement, and debug ETL pipelines to process and manage complex datasets. Leverage big data tools, including Apache Kafka, Spark, and Airflow, to deliver scalable solutions. Collaborate with stakeholders to ensure data quality and alignment with business goals. Utilize programming expertise … experience in data engineering projects Good hands-on experience of designing, implementing, debugging ETL pipeline Expertise in Python, PySpark and SQL languages Expertise with Spark and Airflow Experience of designing data pipelines using cloud native services on AWS Extensive knowledge of AWS services like API Gateway, Lambda, Redshift, Glue ...

generative AI applications. Perform Exploratory Data Analysis (EDA), data mining, and visualization to extract insights. Design and implement Big Data solutions using Hadoop, Spark, PySpark, and Data Lake architectures. Develop and deploy ML models (supervised, unsupervised, tree-based, ensemble methods). Implement deep learning architectures (CNN, RNN, LSTM) using … compliance of AI systems. Required Skills: Analytical Tools: EDA, Data Mining, Visualization (Plotly, Matplotlib, Seaborn) Statistical & Multivariate Analysis Big Data: Hadoop, MapReduce, HDFS, DataBricks, Spark, PySpark DataLake Architecture, AWS Redshift, Kinesis, EMR Machine Learning Supervised Models: Nave Bayes, Logistic Regression, SVM, Linear Regression, KNN, Tree-Based Models: Decision Trees ...

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 ...