1 to 25 of 34 Dask Jobs in England

Professional Expertise Extensive experience with data engineering principles and advanced analytics techniques. Proficiency in programming languages (Python, R, SQL). Experience with data manipulation and analysis tools (Pandas, NumPy, Dask). Strong leadership and communication skills. Ability to lead cross-functional teams and manage stakeholder expectations. Attention to detail and ability to follow defined processes Drive and commitment to learn More ❯

on building scalable and efficient systems Experience with graph (DAG) representation, analysis, and processing using tools like NetworkX Experience with open source distributed computing tools in Python, such as Dask or Ray Proficiency in data processing, analysis, and visualization leveraging best-in-class open source tools, libraries, and frameworks Solid understanding of statistical modeling, machine learning techniques, and their practical More ❯

in a data-driven role, with exposure to: scaling and optimising ML models, training and serving foundation models at scale (federated learning a bonus); distributed computing frameworks (e.g., Spark, Dask) and high-performance computing frameworks (MPI, OpenMP, CUDA, Triton); cloud computing (on hyper-scaler platforms, e.g., AWS, Azure, GCP); building machine learning models and pipelines in Python, using common libraries More ❯

testing, CI/CD, API design, MLOps) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., PyTorch, MLFlow, JAX) Distributed computing frameworks (e.g., Spark, Dask) Cloud platforms (e.g., AWS, Azure, GCP) and HP computing Containerization and orchestration (Docker, Kubernetes) Ability to scope and effectively deliver projects Strong problem-solving skills and the ability to analyse More ❯

commercial experience in designing and implementing systematic trading systems Experience in developing and deploying RESTful APIs and microservices for model serving Familiarity with Big Data technologies such as Ray, Dask, and Spark Experience with data visualization and reporting tools Familiarity with databases and query languages for data extraction and transformation Understanding of and experience with modern software development practices and More ❯

versioning, testing, CI/CD, API design, MLOps) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow) Distributed computing frameworks (e.g., Spark, Dask) Cloud platforms (e.g., AWS, Azure, GCP) and HP computing Containerization and orchestration (Docker, Kubernetes) Strong problem-solving skills and the ability to analyse issues, identify causes, and recommend solutions quickly More ❯

them on real client use cases. Proficient in one of the deep learning stacks such as PyTorch or Tensorflow. Working knowledge of parallelisation and async paradigms in Python, Spark, Dask, Apache Ray. An awareness and interest in economic, financial and general business concepts and terminology. Excellent written and verbal command of English. Strong problem-solving, analytical and quantitative skills. A More ❯

ML/Haskell/F# etc) Nice to Have A ComSci degree from a top rated uni Experience in a fast-paced startup environment Task orchestration frameworks (e.g. Luigi, Dask, Airflow + Celery etc) Experience owning or being involved longer-term in an open-source project Demonstrable Rust experience or keen interest Data pipelines and big data tech Docker: both More ❯

computer programming skills, with knowledge of Python, R, and Java. Experience scaling machine learning on data and compute grids. Proficiency with Kubernetes, Docker, Linux, and cloud computing. Experience with Dask, Airflow, and MLflow. MLOps, CI, Git, and Agile processes. Why you do not want to miss this career opportunity? We are a mission-driven firm that is revolutionising the Insurance More ❯

Computer Science. Minimum of 4 years of experience in designing, developing and deploying production-level deep learning recommendation models with a proven business impact. Fluency in Python, Pandas/Dask, SQL, PyTorch or Tensorflow. Ability to write readable and maintainable code. Strong communication and storytelling skills with both technical and non-technical audiences. Ability to present complex technical subjects to More ❯

leadership and uphold best engineering practices. Requirements for a GenAI Python Engineer : Hands-on experience with Generative AI and Python. Strong skills in Pandas, NumPy, and familiarity with Spark, Dask, and LangChain. Expertise in Kubernetes, backend development, and scalable API engineering. Experience in financial services is a plus. A Bachelor's degree in a technical field (Master's preferred). More ❯

patterns, algorithms, and complexity. Practical experience with automated unit testing, DevOps, and cloud computing. Familiarity with source control and versioning tools. Experience with Python libraries like pandas, numpy, xarray, dask, matplotlib, sqlite, etc., is beneficial. Programming experience in Python and C++, including numerical and data analytics libraries. Knowledge of R, C#, Java, etc., is a plus. Proven problem-solving skills More ❯

AI. - Understanding of ethical AI principles, bias mitigation techniques, and responsible AI practices. - Experience with cloud computing platforms (e.g., AWS, GCP, Azure) and distributed computing frameworks (e.g., Apache Spark, Dask). - Strong problem-solving, analytical, and critical thinking skills. Our inclusive culture empowers Amazonians to deliver the best results for our customers. If you have a disability and need a More ❯

apply, integrate and deploy Machine Learning capabilities and techniques into other systems. Are familiar with the Python data science stack through exposure to libraries such as Numpy , Scipy , Pandas, Dask , spaCy , NLTK, scikit-learn. Take pride in writing clean, reusable, maintainable and well-tested code. Demonstrate proficiency in automation, system monitoring, and cloud-native applications, with familiarity in AWS or More ❯

Join to apply for the Senior Sales Engineer, Financial Services (EMEA) role at Domino Data Lab 4 days ago Be among the first 25 applicants Join to apply for the Senior Sales Engineer, Financial Services (EMEA) role at Domino Data More ❯

including understanding of Linux, security, and networking Cloud templating tools such as Terraform Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch) Experience with distributed computing tools (e.g., Ray, Dask) Experience with model serving tools (e.g., vLLM, KFServing) Experience with building, monitoring, and alerting on logs and metrics Cloud Networking including connectivity, routing, DNS, VPCs, proxies, and load balancers Cloud More ❯

with cloud platforms (GCP, AWS or Azure), especially managed ML services like SageMaker or Vertex AI Proficiency in SQL and working knowledge of distributed computing tools like Spark or Dask Nice to Have: Experience with natural language processing (NLP) e.g., using LLMs, transformers, text classification Familiarity with Graph ML (e.g., for customer network analysis or fraud detection) Exposure to finance More ❯

with cloud platforms (GCP, AWS or Azure), especially managed ML services like SageMaker or Vertex AI Proficiency in SQL and working knowledge of distributed computing tools like Spark or Dask Nice to Have: Experience with natural language processing (NLP) e.g., using LLMs, transformers, text classification Familiarity with Graph ML (e.g., for customer network analysis or fraud detection) Exposure to finance More ❯

with cloud platforms (GCP, AWS or Azure), especially managed ML services like SageMaker or Vertex AI Proficiency in SQL and working knowledge of distributed computing tools like Spark or Dask Nice to Have: Experience with natural language processing (NLP) e.g., using LLMs, transformers, text classification Familiarity with Graph ML (e.g., for customer network analysis or fraud detection) Exposure to finance More ❯

with cloud platforms (GCP, AWS or Azure), especially managed ML services like SageMaker or Vertex AI Proficiency in SQL and working knowledge of distributed computing tools like Spark or Dask Nice to Have: Experience with natural language processing (NLP) e.g., using LLMs, transformers, text classification Familiarity with Graph ML (e.g., for customer network analysis or fraud detection) Exposure to finance More ❯

with cloud platforms (GCP, AWS or Azure), especially managed ML services like SageMaker or Vertex AI Proficiency in SQL and working knowledge of distributed computing tools like Spark or Dask Nice to Have: Experience with natural language processing (NLP) e.g., using LLMs, transformers, text classification Familiarity with Graph ML (e.g., for customer network analysis or fraud detection) Exposure to finance More ❯

Experience working with large geospatial raster and vector datasets, including Earth Observation or climate data. Proficiency with processing large, complex datasets using Python-based geospatial tools (xarray, numpy, scipy, dask, geopandas, OGR, GDAL). Strong quantitative skills with the ability to extract insights from spatial data. Familiarity with modelling concepts from hydrology, atmospheric sciences, or environmental sciences. Desirable Skills Experience More ❯

with cloud platforms (GCP, AWS or Azure), especially managed ML services like SageMaker or Vertex AI Proficiency in SQL and working knowledge of distributed computing tools like Spark or Dask Nice to Have: Experience with natural language processing (NLP) e.g., using LLMs, transformers, text classification Familiarity with Graph ML (e.g., for customer network analysis or fraud detection) Exposure to finance More ❯

or pre/post-doctoral work. OR A Master's in the above subjects with 3-4 years of industrial experience in a relevant competitive environment. Proficiency in Python, Dask, Numpy, Pandas, Keras and PyTorch. Experience withsingle-cell sequencing data Passion for knowledge sharing, mentoring colleagues, and shaping scientific strategy as part of a growingleadership team. What We Value Scientific More ❯

collaborative, and dynamic environment. Nice to haves: Prior experience with PCB design, EDA tools, or related optimization problems. Hands-on experience in high-performance computing environments (e.g., Kubernetes, Ray, Dask). Contributions to open-source projects, publications, or top placements in ML competitions (e.g., Kaggle). Expertise in related fields such as Computer Vision, Representation Learning, or Simulation Environments. More ❯