46 to 70 of 298 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 ❯

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 ❯

is required for this role. Essential Skills & Experience: • Proven experience developing solutions with Power Apps (Canvas and Model-driven apps). • Strong proficiency in Python, including libraries such as Pandas, NumPy, and Flask or FastAPI. • Experience with Microsoft Power Platform, including Power Automate and Dataverse. • Ability to mentor and support junior staff in technical development. • Excellent communication and stakeholder engagement 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 ❯

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 ❯

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 ❯

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 ❯

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 ❯