101 to 125 of 643 Permanent NumPy Jobs

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

but not required). 3+ years of professional experience in machine learning engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining … explainability techniques (e.g., SHAP, LIME). Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

or more of the following database systems – DynamoDB, DocumentDB, MongoDB Demonstrated expertise in unit testing and tools – JUnit, Mockito, PyTest, Selenium. Strong working knowledge of the PyData stack – pandas, NumPy for data manipulation; Jupyter Notebooks for experimentation; matplotlib/Seaborn for basic visualisation. Experience with data analysis and troubleshooting data-related issues. Knowledge of design patterns and software architectures Familiarity … or more of the following database systems – DynamoDB, DocumentDB, MongoDB Demonstrated expertise in unit testing and tools – JUnit, Mockito, PyTest, Selenium. Strong working knowledge of the PyData stack – pandas, NumPy for data manipulation; Jupyter Notebooks for experimentation; matplotlib/Seaborn for basic visualisation. Experience with data analysis and troubleshooting data-related issues. Knowledge of design patterns and software architectures Familiarity More ❯

impossible or extremely difficult to solve. The Technology Core systems are almost all running on Linux and most of the code is in Python, with the full scientific stack: numpy, scipy, pandas, scikit-learn to name a few of the libraries used extensively. For storage, they rely heavily on MongoDB. They use Docker, Kubernetes and Airflow to streamline deployments and … Python, Java, (C++ desirable) Experience of the challenges of dealing with large data sets, both structured and unstructured Used a range of open source frameworks and development tools, e.g. NumPy/SciPy/Pandas, Spark, Kafka, Flink Working knowledge of one or more relevant database technologies, e.g. Oracle, Postgres, MongoDB, ArcticDB. Proficient on Linux Advantageous: An excellent understanding of financial More ❯

AWS, Python Liaise daily with investment professionals to understand requirements and deliver solutions What we’re looking for: Strong Python developer with deep experience using statistical and numerical libraries (NumPy, pandas, SciPy etc.) Proven experience supporting quant or systematic investment strategies Good understanding of infrastructure – ideally AWS and Snowflake – and willingness to own setup and tooling Comfortable working in fast More ❯

AWS, Python Liaise daily with investment professionals to understand requirements and deliver solutions What we’re looking for: Strong Python developer with deep experience using statistical and numerical libraries (NumPy, pandas, SciPy etc.) Proven experience supporting quant or systematic investment strategies Good understanding of infrastructure – ideally AWS and Snowflake – and willingness to own setup and tooling Comfortable working in fast More ❯

AWS, Python Liaise daily with investment professionals to understand requirements and deliver solutions What we’re looking for: Strong Python developer with deep experience using statistical and numerical libraries (NumPy, pandas, SciPy etc.) Proven experience supporting quant or systematic investment strategies Good understanding of infrastructure – ideally AWS and Snowflake – and willingness to own setup and tooling Comfortable working in fast More ❯

related scientific fields. Experience with financial markets (rates, FX, credit). Knowledge of financial mathematics, modeling, and statistics. At least 3 years of development experience with Python (e.g., pandas, numpy) or C Java. Strong analytical and problem-solving skills. Experience working in a production environment. Solid communication skills. Ability to work independently in a fast-paced environment. Detail-oriented, organized More ❯

Demonstrable Rust experience or keen interest Data pipelines and big data tech Docker: both building but running too Wide AWS and infrastructure knowledge, including production support Scientific computing e.g. Numpy/scipy/pandas Just state the word 'Salmon' anywhere in your application, just to prove you can read a job advert. We aim to improve all our colleagues' abilities More ❯

using statistical and machine learning models to contribute to company growth efforts, impacting revenue and other key business outcomesAdvanced understanding of Python and the machine learning ecosystem in Python (Numpy, Pandas, Scikit-learn, LightGBM, PyTorch)Knowledge of SQL and experience with relational databasesAgile, action-oriente Nice to have Apache SparkExperience working in cloud platforms (AWS, GCP, Microsoft Azure)Relevant knowledge More ❯