degree in computer science, electrical engineering, mathematics, or a similar field 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 Experience developing and deploying ML More ❯
Chicago, Illinois, United States Hybrid/Remote Options
Capital One
degree in computer science, electrical engineering, mathematics, or a similar field 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 Experience developing and deploying ML More ❯
a public cloud such as 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 3+ years of people management More ❯
of experience designing and building 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 systems 1+ years of experience More ❯
of experience designing and building 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 systems 1+ years of experience More ❯
of experience designing and building 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 systems 1+ years of experience More ❯
of experience building production-ready 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 2+ years of people leader More ❯
of experience building production-ready 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 2+ years of people leader More ❯
of experience building production-ready 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 2+ years of people leader More ❯
of experience building production-ready 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 2+ years of people leader More ❯
of experience building production-ready 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 2+ years of people leader More ❯
of experience building production-ready 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 2+ years of people leader More ❯
Washington, Washington DC, United States Hybrid/Remote Options
Capital One
with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL) 3+ years of experience with industry recognized ML frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of experience building, scaling, and optimizing ML systems 2+ years of experience More ❯
Dallas, Texas, United States Hybrid/Remote Options
Capital One
with Distributed data/computing tools (MapReduce, Hadoop, Hive, EMR, Kafka, Spark, Gurobi, or MySQL) 3+ years of experience with industry recognized ML frameworks such as scikit-learn, PyTorch, Dask, Spark, or TensorFlow 3+ years of experience building production-ready data pipelines that feed ML models 3+ years of experience building, scaling, and optimizing ML systems 2+ years of experience More ❯
of experience building production-ready 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 2+ years of people leader More ❯
of experience building production-ready 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 2+ years of people leader More ❯
of experience building production-ready 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 2+ years of people leader More ❯
of experience designing and building 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 systems 1+ years of experience More ❯
of experience designing and building 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 systems 1+ years of experience More ❯
of experience designing and building 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 systems 1+ years of experience More ❯
of experience designing and building 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 systems 1+ years of experience More ❯
data pipelines. Experience leveraging data modeling techniques and ability to articulate the trade-offs of different approaches. Experience with one or more data processing technologies (e.g. Flink, Spark, Polars, Dask, etc.) Experience with multiple data storage technologies (e.g. S3, RDBMS, NoSQL, Delta/Iceberg, Cassandra, Clickhouse, Kafka, etc.) and knowledge of their associated trade-offs. Experience with multiple data formats More ❯
or optimising LLMs. Hands-on expertise in C Rust/Go for systems programming, plus Python for model integration. Strong knowledge of distributed runtimes and scheduling frameworks (e.g. Ray, Dask, MPI, or custom equivalents). Experience with GPU cluster management (CUDA, NCCL, Triton Inference Server) and performance tuning across accelerators. Solid grasp of cloud-native orchestration (Docker, Kubernetes, Helm) and More ❯
or optimising LLMs. Hands-on expertise in C Rust/Go for systems programming, plus Python for model integration. Strong knowledge of distributed runtimes and scheduling frameworks (e.g. Ray, Dask, MPI, or custom equivalents). Experience with GPU cluster management (CUDA, NCCL, Triton Inference Server) and performance tuning across accelerators. Solid grasp of cloud-native orchestration (Docker, Kubernetes, Helm) and More ❯
validation, monitoring, and access layers for research/production use. Scale up and productionize research model pipelines into large-scale, reliable distributed compute jobs. Manage distributed compute workflows with Dask, Ray, and other frameworks. Develop Jupyter tooling, templates, and widgets for strategy prototyping and parameter tuning. Implement performance attribution, PnL decomposition, and diagnostic tools. Build dashboards and visualizations (Bokeh, Matplotlib … of crypto or TradFi markets and trading concepts. Nice to Have Experience with crypto exchanges and market microstructure. Hands-on with Bokeh or other interactive viz libraries. Distributed compute (Dask, Ray) experience. ML Stack (JAX, Pytorch, Tensorflow, XGBoost, etc.) experience. Experience with compilers and code generation. Benefits International environment (English is the main language) Pension 100% health coverage Team events More ❯
