23 of 23 Dask Jobs

expertise in some of the following: Python, SQL, Scala, and Java for data engineering. Strong experience with big data tools (Apache Spark, Hadoop, Databricks, Dask) and cloud platforms (AWS, Azure, GCP). Proficient in data modelling (relational, NoSQL, dimensional) and DevOps automation (Docker, Kubernetes, Terraform, CI/CD). Skilled More ❯

AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models More ❯

leading project development efforts from a SCIF. Familiarity with cybersecurity analytics, including PCAP, CVEs, and network monitoring. Experience integrating with technologies such as Spark, Dask, Snowpark, or Kafka. Background in web application stacks (e.g., Flask, Django) or task schedulers (e.g., Airflow, Celery, Prefect). Compensation & Benefits: Competitive salary, equity, and More ❯

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 More ❯

development practices. Knowledge of Apache Spark and similar programming to support streaming data. Experience with some of the following Python libraries: NumPy, Pandas, PySpark, Dask, Apache Airflow, Luigi, SQLAlchemy, Great Expectations, Petl, Boto3, matplotlib, dbutils, koalas, OpenPyXL, XlsxWriter. Experience with monitoring and logging tools (e.g., Prometheus, Grafana, ELK Stack, Splunk More ❯

AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models More ❯

AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models More ❯

AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models More ❯

AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models More ❯

data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications: 1+ years of experience building, scaling, and optimizing ML More ❯

AWS, Azure, or Google Cloud Platform 4+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience developing performant, resilient, and maintainable code 3+ years of experience with data gathering and preparation for ML models More ❯

data-intensive solutions using distributed computing At least 2 years of on-the-job experience with an industry recognized ML frameworks (scikit-learn, PyTorch, Dask, Spark, or TensorFlow) At least 1 year of experience productionizing, monitoring, and maintaining models Preferred Qualifications: 1+ years of experience building, scaling, and optimizing ML More ❯

Azure/GCP and AWS. Experience in automation of performance testing. Data environments exposure is a plus (Airflow, EMR, SageMaker, Ray, Tensorflow, MLflow, Kubeflow, Dask). Working conditions: Occasional out of hour's conferencing with overseas colleagues. Occasional out of hours or weekend work. A workplace that supports & role models More ❯

data pipelines that feed ML models 3+ years of on-the-job experience with an industry recognized ML framework such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 2+ years of experience developing performant, resilient, and maintainable code 2+ years of experience with data gathering and preparation for ML models More ❯

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 More ❯

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 More ❯

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. - Strong communication, collaboration, and leadership skills. Our inclusive culture empowers Amazonians to deliver the best results More ❯

/CD, and modern development workflows Solid understanding of data structures, algorithms, and performance tuning Nice-to-Have: Experience with distributed computing frameworks (e.g. Dask, Spark) Exposure to cloud platforms (AWS, GCP, Azure) Familiarity with SQL and relational databases Experience working in agile environments More ❯

ML models into production environments, including both batch and real-time/streaming contexts Proficiency working with distributed computing frameworks such as Apache Spark , Dask, or similar Experience with cloud-native ML deployment , particularly on AWS , using services like ECS, EKS, Fargate, Lambda, S3, and more Familiarity with orchestration and More ❯

to interpret performance metrics (e.g., CPU, memory, threads, file handles). Knowledge and experience in distributed computing - parallel computation on a single machine like DASK, Distributed processing on Public Cloud. Knowledge of SDLC and experience in working through the entire life cycle of the project from start to end. ABOUT More ❯

C/C++ HPC experience: development and operations of highly distributed software systems and distributed, multi-core data driven processing algorithm development (such as Dask, MPI and/or OpenMP More ❯

IFS is a billion-dollar revenue company with 7000+ employees on all continents. Our leading AI technology is the backbone of our award-winning enterprise software solutions, enabling our customers to be their best when it really matters-at the More ❯

COMPANY OVERVIEW XCEL Engineering, Inc. is an award-winning small business that provides trusted information technology, engineering, consulting and project management solutions and services to federal agencies and organizations. Originally founded in 1971 by professional engineers at the University of More ❯