1 to 25 of 107 Remote Permanent NumPy Jobs

Science, Engineering, AI, or related field. 7+ years of professional software development experience, with at least 3 years in AI/ML. Strong proficiency in Python , including libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch . Solid understanding of ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP More ❯

to the development of quantitative libraries and shared research infrastructure. Qualifications & Skills Essential: Strong expertise in machine learning, statistical modelling, and numerical methods with practical applications. Proficiency in Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) and experience with C++ or Java for high-performance model integration. Solid understanding of Fixed Income products, yield curve modelling, and financial mathematics. Experience More ❯

to the development of quantitative libraries and shared research infrastructure. Qualifications & Skills Essential: Strong expertise in machine learning, statistical modelling, and numerical methods with practical applications. Proficiency in Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) and experience with C++ or Java for high-performance model integration. Solid understanding of Fixed Income products, yield curve modelling, and financial mathematics. Experience More ❯

to the development of quantitative libraries and shared research infrastructure. Qualifications & Skills Essential: Strong expertise in machine learning, statistical modelling, and numerical methods with practical applications. Proficiency in Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) and experience with C++ or Java for high-performance model integration. Solid understanding of Fixed Income products, yield curve modelling, and financial mathematics. Experience More ❯

to the development of quantitative libraries and shared research infrastructure. Qualifications & Skills Essential: Strong expertise in machine learning, statistical modelling, and numerical methods with practical applications. Proficiency in Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) and experience with C++ or Java for high-performance model integration. Solid understanding of Fixed Income products, yield curve modelling, and financial mathematics. Experience More ❯

to the development of quantitative libraries and shared research infrastructure. Qualifications & Skills Essential: Strong expertise in machine learning, statistical modelling, and numerical methods with practical applications. Proficiency in Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow) and experience with C++ or Java for high-performance model integration. Solid understanding of Fixed Income products, yield curve modelling, and financial mathematics. Experience More ❯

you work. The work space itself is also quite nice, and there is an excellent cafeteria! The tech stack on this team is rather huge and includes Python (Pandas, numpy, scipy, scikit-learn, standard libraries, etc.), Python packages that wrap Machine Learning (packages for NLP, Object Detection, etc.), Linux, AWS/C2S, Apache NiFi, Spark, pySpark, Hadoop, Kafka, ElasticSearch, Solr More ❯

you work. The work space itself is also quite nice, and there is an excellent cafeteria! The tech stack on this team is rather huge and includes Python (Pandas, numpy, scipy, scikit-learn, standard libraries, etc.), Python packages that wrap Machine Learning (packages for NLP, Object Detection, etc.), Linux, AWS/C2S, Apache NiFi, Spark, pySpark, Hadoop, Kafka, ElasticSearch, Solr More ❯

of data processing and ML jobs, including the use of IAC to build data pipelines Expert knowledge of Python. An excellent knowledge of basic machine learning libraries, such as NumPy, SciPy, Pandas, Dask, PyTorch, Tensorflow, etc. A proven track record of linking data from multiple systems for scalable productionised solutions with security and monitoring best practices. Experienced with Cloud Security More ❯

loading. Databases: PostgreSQL, NoSQL, Vector Databases, Graph Databases etc. ETL/ELT Concepts Data warehouse concepts SQL Competency in data exploration, analytics, and feature engineering. (Python Specific) Pandas/NumPy/Polars/PySpark Plotly/Matplotlib (some form of data visualization) Data encoding/normalizing/regularizing/etc. Understanding of Deep learning concepts and architectures like CNNs, RNNs More ❯

in the following areas: 1. 2+ Years of professional experience. 2. Strong Python programming skills. 3. Experience with image processing libraries (e.g. OpenCV, PIL, scikit-image) or numerical analysis (NumPy, SciPy). 4. Solid understanding of React/JavaScript/Typescript for web or mobile app development. Desirable skills/requirements 5. Experience with cloud/server management (AWS, Azure More ❯

in the following areas: 1. 2+ Years of professional experience. 2. Strong Python programming skills. 3. Experience with image processing libraries (e.g. OpenCV, PIL, scikit-image) or numerical analysis (NumPy, SciPy). 4. Solid understanding of React/JavaScript/Typescript for web or mobile app development. Desirable skills/requirements 5. Experience with cloud/server management (AWS, Azure More ❯

you work. The work space itself is also quite nice, and there is an excellent cafeteria! The tech stack on this team is rather huge and includes Python (Pandas, numpy, scipy, scikit-learn, standard libraries, etc.), Python packages that wrap Machine Learning (packages for NLP, Object Detection, etc.), Linux, AWS/C2S, Apache NiFi, Spark, pySpark, Hadoop, Kafka, ElasticSearch, Solr More ❯

you work. The work space itself is also quite nice, and there is an excellent cafeteria! The tech stack on this team is rather huge and includes Python (Pandas, numpy, scipy, scikit-learn, standard libraries, etc.), Python packages that wrap Machine Learning (packages for NLP, Object Detection, etc.), Linux, AWS/C2S, Apache NiFi, Spark, pySpark, Hadoop, Kafka, ElasticSearch, Solr More ❯

the OpenAPI specification and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic More ❯

the OpenAPI specification and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic More ❯

the OpenAPI specification and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic More ❯

the OpenAPI specification and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic More ❯

the OpenAPI specification and code generation toolsets for API development. Some experience with Python, modern development techniques, and design patterns. Experience in data science tools and ML tools (e.g., NumPy, pandas, scikit-learn, PyTorch) and open-source contributions (especially Python-based) would be a bonus. Familiarity with CUDA, GPU-based computations, end-to-end neural network training, MLOps, and academic More ❯

deploying machine learning models in production environments. Familiarity with AWS services such as SageMaker, Bedrock, and GlueDemonstrated ability to work with large-scale datasets using tools such as Pandas, NumPy, and SQL. U.S. citizenship required Active TS/SCI w. Polygraph clearance required Must be local to, or willing to relocate to the DMV Metropolitan area Preferred Skills and Experience More ❯

learning, particularly in recommendation systems and deep learning architectures Strong understanding of two-tower neural networks, embedding techniques, and ranking models Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku Experience with ML Ops, including deployment, monitoring, and retraining pipelines Ability to work cross More ❯

machine learning Familiarity with supervised and unsupervised learning, NLP, neural networks, Bayesian statistics, time-series forecasting, collaborative filtering, and deep learning Proficiency in Python and ML libraries (e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Experience with cloud platforms (GCP, AWS, Azure) and tools like Dataiku and Databricks Experience with ML Ops, including deployment, monitoring, and retraining pipelines Ability to More ❯

in recommendation systems and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work More ❯

in recommendation systems and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work More ❯

in recommendation systems and deep learning architectures. Strong understanding of two-tower neural networks, embedding techniques, and ranking models. Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku. Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. Ability to work More ❯