9 of 9 Remote Contract Pandas Jobs

frameworks like Hugging Face Transformers , PyTorch , YOLO , OpenCV , and Pillow Designing and deploying AI services via FastAPI , AWS Lambda , EKS/ECS , and S3 Creating scalable data pipelines with Pandas , NumPy , SQLAlchemy , and Airflow Supporting real-time model inference, edge deployments, and API integrations Working closely with a technical lead in a service-based and serverless architecture Essential Python Engineer More ❯

Python experience, including modern features such as async/await, decorators, and context managers. Knowledge of OCR, Object Detection, LLM solutions Solid grounding in data processing using libraries like Pandas and NumPy. Experience building APIs (FastAPI or similar) and integrating with external services. Familiarity with cloud platforms (AWS preferred), serverless technologies, and containerised deployments. Knowledge of database integration (SQL and More ❯

Learning applications on a cloud platform (GCP ideal, AWS & Azure also acceptable) * Experience with common Python packages for Machine Learning - examples include PyTorch, TensorFlow, XGBoost, scikit-learn, SciPy, NumPy, pandas, etc. * Strong knowledge of SQL and its use for data preparation & feature engineering * Understanding of & practical experience with implementing MLOps principals - including automated model retraining, monitoring & deployment strategies * Some knowledge More ❯

reliability and accuracy. Stay up-to-date with the latest ML research and tools. Required Skills & Experience Strong proficiency in Python and its ML/data libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow or PyTorch). Hands-on experience with Amazon SageMaker , including training, tuning, and deploying models. Solid understanding of machine learning algorithms and statistical methods. Experience with cloud More ❯

up-to-date with emerging trends and technologies in the field of data science. Requirements Proven experience as a data scientist using Python and a range of libraries (Numpy, Pandas, Scikit-Learn, Matplotlib, Plotly etc.). Strong expertise in statistical modelling, machine learning, and data mining techniques. Experience in computer vision is essential. Data engineering (pipelines, databases, infrastructure), ideally with More ❯

with external systems. Deploy scalable AI systems using AWS (Lambda, S3, SQS, EKS/ECS), CDK , and modern DevOps practices. Collaborate on infrastructure and data pipelines using SQLAlchemy, Boto3, Pandas, and Airflow . Contribute to real-time AI services , model versioning, and advanced fine-tuning (LoRA, QLoRA, etc.). AI Engineer requirements: Solid Python skills (3.9+) with deep knowledge of More ❯

quality, documentation, and testing Develop evaluation pipelines and ensure robust quality control across deployments Essential Skills and Experience: Advanced Python programming skills with experience in libraries such as Numpy, Pandas, Scikit-Learn, Langchain, LlamaIndex Deep expertise in Azure and its AI services, including Azure AI Foundry Hands-on experience with GenAI techniques: prompt orchestration, retrieval methods (RAG, knowledge graphs), agentic More ❯

quality, documentation, and testing Develop evaluation pipelines and ensure robust quality control across deployments Essential Skills and Experience: Advanced Python programming skills with experience in libraries such as Numpy, Pandas, Scikit-Learn, Langchain, LlamaIndex Deep expertise in Azure and its AI services, including Azure AI Foundry Hands-on experience with GenAI techniques: prompt orchestration, retrieval methods (RAG, knowledge graphs), agentic More ❯

learning, and data mining. Proficiency in programming languages such as Python, R, or SQL. Experience with machine learning frameworks (eg, TensorFlow, PyTorch, Scikit-learn) and data processing tools (eg, Pandas, Spark). Excellent analytical and problem-solving skills, with a keen eye for detail. Ability to communicate complex findings clearly and effectively to both technical and non-technical stakeholders. Experience More ❯