4 of 4 Remote TensorFlow Jobs in Tyne and Wear

ll work with experienced AI engineers and data scientists to: Build & Train Models : Support the development and training of machine learning and deep learning models using tools like Python, TensorFlow, PyTorch, or Scikit-learn. Explore & Prepare Data : Help clean, transform, and analyse large datasets for AI applications. Experiment & Research : Test new algorithms, perform feature engineering, and help improve model … interest in AI/ML, data science, or applied statistics Solid programming skills in Python (or similar languages) Familiarity with data science or AI libraries such as Pandas, NumPy, TensorFlow, PyTorch, or Scikit-learn Strong problem-solving ability and analytical thinking A willingness to learn and work collaboratively in a team environment Nice to Have (But Not Required): Experience … impact Structured Learning : Receive training and mentoring in AI tools, techniques, and best practices Certification Support : Assistance in pursuing relevant AI/ML certifications (e.g. Google AI, AWS ML, TensorFlow Developer) Career Growth : Opportunities to specialise in areas like NLP, computer vision, or AI engineering Community & Culture : Be part of a collaborative, diverse, and forward-thinking tech team Excellent More ❯

in helping our team develop and deliver ML-powered solutions: Model Development : Assist in building and training machine learning and deep learning models using Python and ML frameworks like TensorFlow, PyTorch, or Scikit-learn Data Preparation : Work on collecting, cleaning, transforming, and analysing large datasets for training and testing models Feature Engineering : Support the design and selection of relevant … or soon-to-be) in Computer Science, Data Science, Engineering, Mathematics, Statistics, Physics, or a related discipline Proficiency in Python and familiarity with ML libraries such as Scikit-learn, TensorFlow, or PyTorch Strong understanding of basic machine learning concepts and algorithms (e.g. regression, classification, decision trees) Good grasp of data structures, algorithms, and programming fundamentals. Analytical mindset and strong … creativity, experimentation, and collaboration Excellent Company Benefits 25+ Days Annual Leave + bank holidays Flexible/Hybrid Working Options Annual Bonus Scheme Support for Certifications and Training Courses (e.g., TensorFlow Developer, AWS ML Speciality) Private Medical & Mental Health Support Tech Budget – choose your own laptop, setup, and productivity tools Matched Pension Contributions Cycle-to-Work Scheme & Commuter Benefits Hackathons More ❯

OPS Engineer to join our growing teams in Newcastle or Erskine. Key Responsibilities Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed More ❯

machine learning models using modern frameworks and libraries. Collaborate with data scientists, engineers, and stakeholders to translate business requirements into technical solutions. Optimize and deploy models using tools like TensorFlow Serving, TorchServe, ONNX, and TensorRT. Build and manage ML pipelines using MLflow, Kubeflow, and Azure ML Pipelines. Work with large-scale data using PySpark and integrate models into production … senior team members in identifying and addressing data science opportunities. Required Skills & Experience Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed … Excellent problem-solving skills and ability to work independently or in a team. Strong proficiency in Python and ML libraries such as: pandas, NumPy, scikit-learn XGBoost, LightGBM, CatBoost TensorFlow, Keras, PyTorch Experience with model deployment and serving tools: ONNX, TensorRT, TensorFlow Serving, TorchServe Familiarity with ML lifecycle tools: MLflow, Kubeflow, Azure ML Pipelines Experience working with distributed More ❯