applications and technical processes within a technical discipline (e.g., cloud, artificial intelligence, machine learning, mobile, etc.) Preferred qualifications, capabilities, and skills Familiarity with modern front-end technologies Familiarity with apache and tomcat-based applications. Exposure to cloud technologies and ansible Evolven exposure is a plus ABOUT US J.P. Morgan is a global leader in financial services, providing strategic advice More ❯
techniques You might also have: Familiarity with data visualization tools and libraries (e.g., Power BI) Background in database administration or performance tuning Familiarity with data orchestration tools, such as Apache Airflow Previous exposure to big data technologies (e.g., Hadoop, Spark) for large data processing Experience with ServiceNow integration More ❯
Meta, Amazon , OpenAI) Proficiency with essential data science libraries including Pandas, NumPy, scikit-learn, Plotly/Matplotlib, and Jupyter Notebooks Knowledge of ML-adjacent technologies, including AWS SageMaker and Apache Airflow. Strong skills in data preprocessing, wrangling, and augmentation techniques Experience deploying scalable AI solutions on cloud platforms (AWS, Google Cloud, or Azure) with enthusiasm for MLOps tools and More ❯
Glasgow, Scotland, United Kingdom Hybrid / WFH Options
Venesky Brown
fine-tuning techniques including LoRA, QLoRA, and parameter efficient methods - Multi-modal AI systems combining text, image, and structured data - Reinforcement Learning from Human Feedback (RLHF) for model alignment - Apache Airflow/Dagster for ML workflow orchestration and ETL pipeline management - Model versioning and experiment tracking (MLflow, Weights & Biases) - Real-time model serving and edge deployment strategies - A/ More ❯
milton, central scotland, united kingdom Hybrid / WFH Options
Venesky Brown
fine-tuning techniques including LoRA, QLoRA, and parameter efficient methods - Multi-modal AI systems combining text, image, and structured data - Reinforcement Learning from Human Feedback (RLHF) for model alignment - Apache Airflow/Dagster for ML workflow orchestration and ETL pipeline management - Model versioning and experiment tracking (MLflow, Weights & Biases) - Real-time model serving and edge deployment strategies - A/ More ❯
paisley, central scotland, united kingdom Hybrid / WFH Options
Venesky Brown
fine-tuning techniques including LoRA, QLoRA, and parameter efficient methods - Multi-modal AI systems combining text, image, and structured data - Reinforcement Learning from Human Feedback (RLHF) for model alignment - Apache Airflow/Dagster for ML workflow orchestration and ETL pipeline management - Model versioning and experiment tracking (MLflow, Weights & Biases) - Real-time model serving and edge deployment strategies - A/ More ❯