5 of 5 Remote/Hybrid TensorFlow Jobs in Southampton

Core Technical Skills 3+ years of experience in Machine Learning, Data Science, or related roles. Strong programming skills in Python. Experience with ML frameworks: TensorFlow, PyTorch, scikit-learn, XGBoost. Solid understanding of ML algorithms, statistics, and evaluation metrics. Experience deploying ML models into production environments. Data & Engineering Skills Strong ...

maintainable code Solid understanding of ML fundamentals. For example feature engineering, model selection, handling imbalanced data, choosing and interpreting metrics Experience with PyTorch or TensorFlow GenAI specific Hands on experience with LLM APIs or open source models such as Llama or Mistral Experience building RAG systems with vector databases ...

product setting Strong knowledge of large language models (LLMs), embeddings, fine-tuning, and evaluation methods Advanced Python skills and experience with frameworks like PyTorch, TensorFlow, and HuggingFace Experience building full ML pipelines from data ingestion to deployment Solid software engineering practices including testing, version control, and CI/ ...

ensemble models. Experience in manipulating and interpreting data from disparate sources. Proficient in Python coding and core data science libraries, such as Pandas, TensorFlow, Scikit-learn etc. Ideally previous experience with Snowflake and DBT. Experience with Cloud Computing (AWS, GCP, Azure) - Ideally in AWS. Creativity and innovative thinking ...

regulated environment with sensitive data. You'll work with engineering to move models from idea to production. Tech Stack: Python, scikit-learn, PyTorch, TensorFlow/Keras, LangChain, Pydantic, Spark, Kafka, Databricks, MLflow, Azure, Docker, Kubernetes. Salary: Up to £100k Working Environment: Fully Remote in UK What … Research, prototype, and deploy LLM use cases (Q&A, summarisation, document processing) Build and tune models using scikit-learn, PyTorch, TensorFlow/Keras, and XGBoost Create data pipelines for batch and streaming with Spark and Kafka Use Databricks and MLflow for experiments, deployment, and monitoring What you'll bring ...