51 to 75 of 251 Permanent Pandas Jobs

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

GitHub Actions, CircleCI - depending on team) Monitoring/Logging (CloudWatch, Prometheus, Grafana - nice-to-have) Data/Scientific Computing/ML Tools Python libraries for data processing, visualization, ML (Pandas, NumPy, Matplotlib, scikit-learn, PyTorch, TensorFlow) Robotics frameworks or internal research computing tools (if applicable) Strong Communication Skills - able to clearly articulate technical concepts to peers, leadership, and cross-functional More ❯

must have proven expertise as an AI Engineer, with a track record of leading initiatives and deploying effective machine learning solutions. Proficiency in Python and libraries, plus tools like Pandas, NumPy, and SQL, is essential. Experience defining value-driven AI strategies and guiding teams on best practices is required, along with knowledge of software principles, API development, CI/CD More ❯

Vision (e.g., image processing, analysis, instance segmentation, OCR, deepfake detection) Game AI (Specific AI for intelligent opponents, understanding game states, actions, rewards) Data Science & Engineering Data Analysis & Manipulation (including Pandas, Matplotlib, Seaborn, NumPy, statistical analysis, general data processing, visualization libraries) Database Management (SQL, NoSQL, SQLite, data storage Algorithms & Mathematics Algorithms (General and specific like Monte Carlo Tree Search (MCTS), A More ❯

and innate curiosity to learn new things Preferred qualifications Background in traditional finance or digital assets, ideally in trading domain Hands-on experience with Python libraries and frameworks (NumPy, Pandas, Airflow, FastAPI, Flask, SQLAlchemy) Highly proficient in asynchronous, event driven distributed systems Working knowledge of cloud-native architectures, GCP preferred Experience in Go and working with real-time data streams More ❯

and innate curiosity to learn new things Preferred qualifications Background in traditional finance or digital assets, ideally in trading domain Hands-on experience with Python libraries and frameworks (NumPy, Pandas, Airflow, FastAPI, Flask, SQLAlchemy) Highly proficient in asynchronous, event driven distributed systems Working knowledge of cloud-native architectures, GCP preferred Experience in Go and working with real-time data streams More ❯

Strong understanding of operational excellence in areas like networking, database performance, and system resilience Experience with real-time analytics platforms Familiarity with big data tools and frameworks, such as Pandas, Polars, PyArrow, Kafka, PostgreSQL, and DeltaTable Background in trading or financial markets is a plus, but not required WHAT YOU'LL GET: The chance to work alongside best-in-class More ❯

flows and ML issues in live production environments. We’re looking for individuals with: Experience: Proven background as a Machine Learning Engineer. Technical Skills: Strong in SQL and Python (Pandas, Scikit-learn, Jupyter, Matplotlib). Data transformation & manipulation : experience with Airflow, DBT and Kubeflow Cloud: Experience with GCP and Vertex AI (developing ML services). Expertise: Solid understanding of computer More ❯

machine 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 More ❯

for a seasoned mid-level Software Engineer with up to 6+ years of hands-on Python experience. Familiarity with AWS Serverless and related technologies would be advantageous. Strengths in Pandas, Polars, Pytest, Postgres, and CI/CD is essential. If you're interested in Agile methodologies, and have a curiosity about DDD and Event-Driven architectures, you'd fit right More ❯

for a seasoned mid-level Software Engineer with up to 6+ years of hands-on Python experience. Familiarity with AWS Serverless and related technologies would be advantageous. Strengths in Pandas, Polars, Pytest, Postgres, and CI/CD is essential. If you're interested in Agile methodologies, and have a curiosity about DDD and Event-Driven architectures, you'd fit right More ❯

learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data analytics, time-series forecasting, or computer vision experience Infrastructure: AWS/GCP/Azure, Docker, Kubernetes, MLflow More ❯

learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data analytics, time-series forecasting, or computer vision experience Infrastructure: AWS/GCP/Azure, Docker, Kubernetes, MLflow More ❯

1st class - 2;1 Degree in Comp Sci or STEM subject from a Top ranked University 3+ years of experience in Python development Tech: Python, FastAPI, Pydantic, PostgreSQL, Numpy, Pandas, AWS DevOps tools: Kubernetes, Docker,Terraform, Jenkins Very strong software engineering principles Enthusiasm for startup environment and cross-functional teams Passion for automation and data infrastructure More ❯

1st class - 2;1 Degree in Comp Sci or STEM subject from a Top ranked University 3+ years of experience in Python development Tech: Python, FastAPI, Pydantic, PostgreSQL, Numpy, Pandas, AWS DevOps tools: Kubernetes, Docker,Terraform, Jenkins Very strong software engineering principles Enthusiasm for startup environment and cross-functional teams Passion for automation and data infrastructure More ❯

and 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 More ❯

visualisation libraries (Matplotlib, Seaborn.) SQL for data extraction and manipulation. Experience working with large datasets. Technical Skills Proficiency in cloud computing and python programming. Familiarity with Python libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linear algebra principles for modelling and optimisation. Calculus for More ❯

visualisation libraries (Matplotlib, Seaborn.) SQL for data extraction and manipulation. Experience working with large datasets. Technical Skills Proficiency in cloud computing and python programming. Familiarity with Python libraries like Pandas, NumPy, scikit-learn. Experience with cloud services for mode training and deployment. Machine Learning Fundamentals Statistical concepts for robust data analysis. Linear algebra principles for modelling and optimisation. Calculus for More ❯

data structures, algorithms, and software engineering best practices Track record of designing scalable, production-grade systems Excellent problem-solving, collaboration, and communication skills Nice to Have Experience with NumPy, Pandas, Cython, or Numba Exposure to market microstructure, risk modelling, or quantitative research Experience developing and maintaining live trading bots or algo execution systems Background in mentoring or technical leadership within More ❯