1 to 25 of 77 TensorFlow Jobs in the Thames Valley

engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g. … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g. … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g. … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g. … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

engineering. 2+ years of leadership or technical mentoring experience. Strong expertise in Python for machine learning (Pandas, NumPy, scikit-learn, etc.). Experience with deep learning frameworks such as TensorFlow, PyTorch, or JAX. Strong understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning). Experience building and maintaining ML pipelines and data pipelines. Proficiency in model deployment techniques (e.g. … Familiarity with reinforcement learning or generative AI models. Tools & Technologies: Languages: Python, SQL (optionally: Scala, Java for large-scale systems) Data Processing: Pandas, NumPy, Apache Spark, Beam Model Serving: TensorFlow Serving, TorchServe, FastAPI, Flask Experiment Tracking & Monitoring: MLflow, Neptune.ai, Weights & Biases #J-18808-Ljbffr More ❯

financial services industry. Strong understanding of the mathematical foundations of deep learning, including multivariate calculus, linear algebra, and optimization techniques. Proficient in Python and deep learning frameworks such as TensorFlow and PyTorch. Experience with CUDA kernels and GPU profiling is a plus. Excellent communication skills, with the ability to present complex technical ideas to both technical and non-technical More ❯

customers, and beyond. What will make you stand out: • Experience working in an analytics role in the gambling industry. • Experience with CRM data analysis and customer segmentation. • Knowledge of tensorflow/pytorch. • Expertise in using data visualization tools such as Google Looker and working with Google's BigQuery. • Experience in design and evaluation of A/B tests. • Familiarity More ❯

datasets using tools like Pandas, NumPy, or Spark. At least 2 years' experience with machine learning, deep learning, or AI systems. Familiarity with key libraries and frameworks such as TensorFlow, Scikit-learn, PyTorch, Transformers, LangChain, BeautifulSoup, and OpenCV. Experience with AI APIs and platforms (e.g., OpenAI, Bedrock, Gemini, Anthropic). Knowledge of cloud infrastructure (ideally AWS), Kubernetes, and relevant More ❯

learning to real world commercial problems Experience bringing live services using machine learning and python to production. Expert knowledge of Python and relevant libraries (numpy, pandas, matplotlib, Scikit-learn, tensorflow, etc...) knowledge in other programming languages is valuable, but this is primarily a Python shop. Experience with things like CI/CD pipelines, Docker or similar, cloud hosting, good More ❯

years in a leadership or senior role. Proven experience in a startup or fast-paced environment. Strong proficiency in Python, SQL, and data science libraries (e.g., scikit-learn, pandas, TensorFlow/PyTorch). Experience working with financial data, risk modelling, or algorithmic trading is a plus. Familiarity with cloud platforms (AWS, GCP, or Azure) and modern data stack tools More ❯

such as Python, R, C++, Rust or Java, and their associated security considerations. Coding experience with AI & ML, deep learning and data manipulation techniques, libraries, and frameworks such as TensorFlow, PyTorch, Jax, and scikit-learn. Personal Attributes Drive and lead continuous improvement with energy and passion Displays high levels of self-awareness and emotional intelligence in all situations Strong More ❯

learning to real world commercial problems Experience bringing live services using machine learning and python to production. Expert knowledge of Python and relevant libraries (numpy, pandas, matplotlib, Scikit-learn, tensorflow, etc...) knowledge in other programming languages is valuable, but this is primarily a Python shop. Experience with things like CI/CD pipelines, Docker or similar, cloud hosting, good More ❯

4+ years of relevant industry experience. Strong expertise in deep learning, neural networks, and generative models (GANs, diffusion models). Practical experience with modern machine learning frameworks (e.g., PyTorch, TensorFlow). Advanced programming skills in Python . Strong problem-solving, analytical, and communication skills. Demonstrated ability to work effectively in multidisciplinary, fast-paced, research-driven teams. Preferred Qualifications Experience More ❯

pricing, AI, data science, or algorithm design, with a track record of building and deploying real-time pricing or recommendation systems Deep technical knowledge of machine learning frameworks (e.g., TensorFlow, PyTorch), cloud platforms (AWS, GCP, Azure), and big data tools (e.g., Spark, Hadoop) Experience designing and/or implementing business-critical operational algorithms Clear communication skills; experienced in communicating More ❯

Deep understanding of computer vision techniques for detection and localisation. Strong experience working with embedded or constrained compute platforms. Proficiency in Python and major machine learning frameworks (e.g., PyTorch, TensorFlow). Experience with version control (Git), containerisation (Docker), and cloud technologies (e.g., AWS). Experience with building and maintaining end-to-end ML pipelines. Degree (BSc, MSc, or PhD More ❯

AI, particularly in LLM and RAG technologies, with knowledge of LLM Agents, explainable AI and/or graph ML as a plus. Proficiency in Python, PyTorch and/or Tensorflow, and popular data science libraries, as well as development skills with Docker, Linux, GitHub/Gitlab, GPUs, and cloud services. Exposure to knowledge graphs and graph databases such as More ❯

background in digital signal processing (DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong problem-solving skills with the More ❯

background in digital signal processing (DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong problem-solving skills with the More ❯

background in digital signal processing (DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong problem-solving skills with the More ❯

background in digital signal processing (DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong problem-solving skills with the More ❯

background in digital signal processing (DSP) and machine learning applied to audio. Proficiency in programming languages such as Python, C++, and MATLAB. Hands-on experience with deep learning frameworks (TensorFlow, PyTorch, etc.). Understanding of real-time and embedded audio processing techniques. Experience working with generative AI models for audio synthesis and transformation. Strong problem-solving skills with the More ❯

Responsibilities: Develop and manage automated machine learning pipelines, CI/CD workflows, and orchestration frameworks for production-ready systems. Design and implement robust model deployment using platforms like TorchServe, TensorFlow Serving, or Triton for reliable inference delivery. Create low-latency, high-throughput inference systems with a focus on performance and scalability. Implement seamless deployment processes with A/B More ❯

/PhD in Mathematics, Statistics, Computer Science or a related field. Proven experience designing or delivering large-scale pricing, AI or recommendation systems. Deep technical knowledge of ML frameworks (TensorFlow, PyTorch), cloud platforms (AWS, GCP, Azure), and big data tools (Spark, Hadoop). Demonstrated success in building business-critical, real-time algorithmic solutions. Strong communication and stakeholder engagement skills More ❯

and data-driven features into 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 Airflow, Spark, or Kafka. Strong More ❯

insights. Machine Learning Engineer Key Skills Required: Comprehensive understanding of the full machine learning lifecycle, from development to production. Experience deploying machine learning models using frameworks like Scikit-learn, TensorFlow, or PyTorch. Proficiency in Python and adherence to software engineering best practices. Strong technical expertise in cloud architecture, security, and deployment, with experience in Azure. Hands-on experience with More ❯