1 to 25 of 99 TensorFlow Jobs in the South East

methods, and predictive modeling Experience with NLP techniques for text analysis, classification, and information extraction Knowledge of deep learning frameworks such as PyTorch or TensorFlow Experience with data visualization tools (Matplotlib, Seaborn, Plotly, or similar) Strong analytical mindset with a focus on solving real-world problems Excellent communication skills More ❯

learning, and neural networks. Strong programming skills in languages such as Python, R, or Java Familiarity with AI libraries, frameworks, and tools such as TensorFlow, PyTorch, or Keras. Proven understanding of cloud computing platforms (e.g., AWS, Azure, Google Cloud) and experience deploying AI models on these platforms. Solid understanding More ❯

a production environment, MLOps and model integration into larger scale applications. Experience with Machine and Deep Learning libraries such as Scikit-learn, XGBoost, MXNet, TensorFlow or PyTorch Exposition to GenAI and solid understanding of multimodal AI via HuggingFace, Llama, VertexAI, AWS Bedrock or GPT Knowledge of data pipeline and More ❯

and developing custom solutions using large language models (LLMs) for business use cases. Proficient in Python-based AI/ML development using frameworks like TensorFlow, PyTorch, and Scikit-learn. LLM Orchestration and Development Expertise in building LLM-powered applications using frameworks such as LangChain and LangGraph, including prompt engineering More ❯

MLOps, DevOps, or ML Engineering roles Proven expertise deploying and scaling Generative AI models (GPT, Stable Diffusion, BERT) Proficiency with Python and ML frameworks (TensorFlow, PyTorch, Hugging Face) Strong cloud platform experience (AWS, GCP, Azure) and managed AI/ML services Practical experience with Docker, Kubernetes, and container orchestration More ❯

through multiple release cycles Strong understanding of data science, machine learning concepts, and analytics capabilities Experience with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, etc.) Experience with MLOps practices (e.g., model deployment, monitoring, retraining workflows) for operationalizing machine learning models effectively Excellent communication skills with More ❯

how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, Markov chains, etc. Experience using specialized machine learning libraries e.g. Fastai, Keras, Tensorflow, pytorch, sci-kit learn, huggingface, etc. Must demonstrate the capacity of reading, understanding and implementing new techniques in the field of machine learning as More ❯

related field (or equivalent experience). Preferred Qualifications: Advanced degree (Master's or Ph.D.) in a relevant field. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch). Knowledge of data visualization tools (e.g., Tableau, Power BI). Familiarity with version control systems (e.g., Git). More ❯

Skills required: Programming: Proficiency in Python (preferred) and/or other relevant languages (e.g., R, Java, C++). Machine Learning & AI Frameworks: Experience with TensorFlow, PyTorch, Scikit-learn, or similar libraries. Data Manipulation & Analysis: Strong skills in Pandas, NumPy, and SQL for handling and analysing large datasets. Cloud Computing More ❯

with a deep understanding of machine learning algorithms, deep learning, and generative models. Advanced AI Skills and Testing: Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch), hands-on experience in deploying AI/ML solutions as a service/REST API on Cloud or Kubernetes, and proficiency in testing More ❯

performance. Requirements: Bachelor’s, Master’s, or PhD in Computer Science, Data Science, Bioinformatics, or related field. Proficiency in Python and ML frameworks (e.g., TensorFlow, PyTorch). Experience with bioinformatics tools (e.g., Biopython, RDKit). Strong knowledge of statistical models, deep learning, and data preprocessing. Familiarity with cloud platforms More ❯

ML workloads. Strong proficiency with Docker, Kubernetes, and infrastructure automation (Terraform, CloudFormation). Solid programming skills in Python and familiarity with ML frameworks like TensorFlow, PyTorch . Experience designing CI/CD pipelines for ML workflows and deployment automation. Exposure to LLM Ops , including managing fine-tuning and deployment More ❯

software engineering knowledge, including data structures, algorithms, system design, and OOP. You have advanced knowledge of LLM architectures and ML/DL frameworks (e.g. TensorFlow, PyTorch, LangChain, Keras, scikit-learn). You're ready to design, deploy and maintain production-grade Machine Learning systems. You're willing to champion More ❯

you will bring: Essential: 5+ years of experience in data science, machine learning, or AI innovation. Strong coding skills in Python (e.g., Pandas, NumPy, TensorFlow, PyTorch) and SQL. Proven experience deploying ML models in production environments. 3+ years in a leadership or mentorship role within AI or data teams. More ❯

as well as cloud-based data storage solutions (e.g., AWS S3, Google Cloud Storage). Experience with AI/ML tools and frameworks (e.g., TensorFlow, PyTorch) and integrating data pipelines with these tools. Familiarity with containerization technologies (e.g., Docker, Kubernetes) and cloud platforms (e.g., AWS, GCP, Azure). Strong More ❯

in machine learning/NLP roles, with recent focus on LLMs and/or GenAI. Strong proficiency in Python, deep learning frameworks (PyTorch or TensorFlow), and GenAI libraries (LangChain, LlamaIndex, Transformers). Hands-on experience with vector search, embedding models, and retrieval pipelines. Familiarity with prompt engineering, prompt tuning More ❯

frameworks like Streamlit) for dashboard creation. Experience with Machine Learning model development and data science workflows (including frameworks such as scikit-learn, PyTorch, or TensorFlow). Experience in Quantitative Finance or strong interest in mathematical/financial modeling, derivatives pricing, or algorithmic trading. Familiarity with ETRM platforms (e.g., OpenLink More ❯

Able to explain complex ideas simply, and work well in cross-functional teams Tech You'll Work With ML & Data Science Python (primary language) TensorFlow, PyTorch, or Keras NumPy, pandas Data pipelines (Azure Data Factory, Airflow, etc.) Applied ML: NLP, CV, transformers, GANs, time series, etc. Engineering & Cloud Azure More ❯

understanding of industry trends, concepts, opportunities, threats & constraints. Experience & knowledge of GenAI, predictive analytics, or automation workflows in enterprise environments. Familiarity with NLP frameworks (TensorFlow, PyTorch) and LLM fine-tuning techniques. ITIL certification and/or AI/ML certifications (AWS, Google Cloud). Experience with implementing scripted web More ❯

years of experience in machine learning engineering, with a strong focus on productionizing ML models and MLOps. Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Strong experience with cloud platforms (AWS, GCP, or Azure) and containerization (Docker, Kubernetes). Hands-on experience with CI/ More ❯

coursework in machine learning, deep learning, or AI techniques (e.g., supervised learning, neural networks, NLP). Proficiency in Python and libraries like Scikit-learn, TensorFlow, PyTorch, or Hugging Face Transformers. Familiarity with data preprocessing, model evaluation, and deploying models in real-world environments. A passion for AI innovation and More ❯

Implementing MLOps best practices for seamless model deployment, monitoring, and iteration. What We’re Looking For: 🔹 Strong Python skills – You know your way around TensorFlow, PyTorch, or Hugging Face. 🔹 Experience with LLMs, NLP, or recommendation algorithms . 🔹 Familiarity with MLOps, APIs, and scalable cloud solutions . 🔹 Passion for AI More ❯

competitive coding background (e.g., ACM/ICPC, NOI/IOI, Top Coder, Kaggle). Technical Skills : Expertise in machine learning frameworks (e.g., scikit-learn, TensorFlow, PyTorch), Generative AI technologies, and libraries like Langchain, Weaviate, Langgraph, LlamaIndex. Track Record : Demonstrated success in applying data science and machine learning to solve More ❯

production. Your Profile: Experience in both data engineering and machine learning, with a strong portfolio of relevant projects. Proficiency in Python with libraries like TensorFlow, PyTorch, or Scikit-learn for ML, and Pandas, PySpark, or similar for data processing. Experience designing and orchestrating data pipelines with tools like Apache More ❯

AI solutions into business workflows. Required Qualifications & Skills Strong experience in AI, NLP, and machine learning algorithms. Proficiency in Python and frameworks such as TensorFlow, PyTorch, or Hugging Face. Hands-on experience with generative AI and LLM fine-tuning . Experience deploying AI applications on Azure (e.g., Azure ML More ❯