11 of 11 Remote Dask Jobs

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 More ❯

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 More ❯

datasets and time series data and perform calculations with at least one modern programming language like Python (utilizing packages like scikit-learn, pandas, or dask), R (utilizing packages like caret, dplyr, or data.table), or other modern language. • Ability to apply, modify and formulate algorithms and processes to solve computational financial More ❯

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 More ❯

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 More ❯

and ecosystems Ability to understand, apply, and deploy machine learning capabilities and techniques Experience with Python data science libraries such as Numpy, Scipy, Pandas, Dask, spaCy, NLTK, scikit-learn Commitment to writing clean, reusable, maintainable, and well-tested code Desire to learn and embrace new and emerging technologies Understanding of More ❯

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 More ❯

many nuanced trade offs and varied opinions. Experience in a range of tools sets comparable with our own: Database technologies: SQL, Redshift, Postgres, DBT, Dask, airflow etc. AI Feature Development: LangChain, LangSmith, pandas, numpy, sci kit learn, scipy, hugging face, etc. Data visualization tools such as plotly, seaborn, streamlit etc More ❯

many nuanced trade offs and varied opinions. Experience in a range of tools sets comparable with our own: Database technologies: SQL, Redshift, Postgres, DBT, Dask, airflow etc. AI Feature Development: LangChain, LangSmith, pandas, numpy, sci kit learn, scipy, hugging face, etc. Data visualization tools such as plotly, seaborn, streamlit etc More ❯

code to achieve performance breakthroughs. Required Skills Understanding of Linux systems, performance analysis tools, and hardware optimisation techniques Experience with distributed training frameworks (Ray, Dask, PyTorch Lightning, etc.) Expertise with Python and/or C/C++ Development with machine learning frameworks (JAX, Tensorflow, PyTorch etc.) Passion for profiling, identifying More ❯

Company Description 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 More ❯