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 ❯
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 Production ML Systems: ApacheAirflow/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 ❯
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 - ApacheAirflow/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 - ApacheAirflow/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 - ApacheAirflow/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 ❯
Edinburgh, Midlothian, Scotland, United Kingdom Hybrid / WFH Options
McGregor Boyall
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 skills and experience More ❯
our platform. Take ownership of specific ML features or components and drive them from concept to production and iteration. Work with leading tools such as GCP Vertex AI, BigQuery, Airflow, and emerging ML technologies. Be a part of a friendly, diverse, innovative, international team and workplace that encourages learning and growth. Who you are: Experience working in a Data More ❯
Edinburgh, Midlothian, Scotland, United Kingdom Hybrid / WFH Options
McGregor Boyall
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 async More ❯