26 to 50 of 53 TensorFlow Jobs in Slough

investors and engineers to forecast key company KPIs, design real-time dashboards, and develop best-in-class data infrastructure. Key Requirements Strong Python (pandas, NumPy, scikit-learn; PyTorch/TensorFlow a plus) and SQL skills Experience applying advanced analytics or ML to real-world data (finance, fintech, or forecasting contexts ideal) Proficiency with BI tools (Tableau or similar More ❯

Learning (policy optimisation, reward modelling, RLHF). Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs). Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow). Proficiency in Python and standard ML libraries. Solid foundations in probability, optimisation, and statistics. Experience working with large-scale distributed training on GPUs/TPUs. If this sounds More ❯

data scientists. What You’ll Bring 🔥 Deep expertise in machine learning and statistical modelling ⚙️ Skilled with core data science tools (NumPy, Pandas, Scikit-Learn) and deep learning frameworks (PyTorch, TensorFlow) 💡 Proven track record delivering impactful AI/ML projects (e.g. forecasting, recommendation systems, or optimisation) 📈 Experienced project lead with strong technical decision-making and architecture ownership 🗣️ Excellent communicator — able More ❯

or ECCV). Deep experience with modern vision architectures such as YOLO , Vision Transformers , and EVA . Strong command of Python and core ML libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Familiarity with MLOps practices and evaluation metrics (Accuracy, Recall, F1, IoU, etc.). Excellent communication and problem-solving skills; ability to engage with both technical and non More ❯

desirable in a model. Familiarity with Python and the packages widely used in data science and machine learning. Developers should be familiar with libraries like NumPy, pandas, scikit-learn, TensorFlow, and PyTorch. Familiarity with best practice in Machine Learning workflows and MLOps tools. Fluency in validation and evaluation framework and metrics frameworks for machine learning such as Accuracy, Recall More ❯

regulatory requirements, and operational challenges. Hands-on expertise with cloud platforms (AWS, Azure, Google Cloud) and scalable, secure data infrastructures. Skilled in analytics, problem-solving, and applying machine learning (TensorFlow, PyTorch, Scikit-learn) to business use cases. Excellent communication and stakeholder management, comfortable engaging with C-level executives. Please note that this role does not offer visa sponsorship If More ❯

model reasoning and user experience. Skills & Experience: Strong hands-on experience deploying ML models in production environments. Excellent programming skills in Python and familiarity with ML/DL libraries (TensorFlow, PyTorch, scikit-learn, Pandas). Practical experience with RAG or agentic AI frameworks (LangChain, LlamaIndex). Experience working with LLM APIs (e.g. Hugging Face, OpenAI). Exposure to conversational More ❯

versioning, and reproducible experimentation. You’ll Bring Strong experience with LLMs, generative, or multimodal models , ideally involving large-scale training or evaluation. Hands-on fluency in PyTorch, JAX, or TensorFlow , with experience in DeepSpeed, Megatron, FSDP, or similar . Understanding of distributed training, parallelism strategies , and scaling laws . Familiarity with post-training methods (RLHF, RLAIF, DPO, or alignment More ❯

prompt orchestration and tool calling. Retrieval-Augmented Generation (RAG) for dynamic context injection. Understanding of user-centric design for AI interfaces and intelligent automation. Experience with AI frameworks (PyTorch, Tensorflow, Hugging Face etc.). Preferred Skills Preferred knowledge of AWS, particularly AWS Bedrock for LLM deployment and orchestration. Self-motivated with a strong growth mindset. Pay range and compensation More ❯

move from concept to code without getting lost in the theory. You’ve already built or deployed real-world AI systems. You understand LLMs, NLP, and ML frameworks like TensorFlow, PyTorch, or LangChain. You know your way around Azure, AWS, or GCP, and you’re confident designing APIs, microservices, and data pipelines. Maybe you’ve come from an academic More ❯

Azure, or Google Cloud). Strong analytical mindset with the ability to translate complex data insights into clear business impact. Working knowledge of machine learning and advanced analytics (e.g., TensorFlow, PyTorch, Scikit-learn). Exceptional stakeholder management skills, comfortable engaging with C-suite executives and senior investors. Strong knowledge of data governance and compliance frameworks (GDPR, CCPA). Thrive More ❯

Requirements: PhD or equivalent experience in ML, AI, CS, physics, or mathematics Strong publication record (NeurIPS, ICML, ICLR, etc.) Proficient in Python, C++, and deep learning frameworks (e.g., PyTorch, TensorFlow) Solid grasp of ML techniques; independent and team-oriented mindse Preferred: Experience in LLMs, reinforcement learning, or chip design Familiarity with JAX and optimization frameworks Why Join Us: Work More ❯

AI (recommendation systems, data mining, or similar). Proven track record of building or deploying GenAI/LLM systems into production. Strong Python skills, with experience in PyTorch or TensorFlow . Understanding of MLOps practices (evaluation, monitoring, scaling). Master’s (or equivalent experience) in Computer Science, AI, ML, or related field. ⭐ Bonus points for: experience designing annotation schemas More ❯

and Confluence (or similar). Able to work from design to implementation and back efficiently. Strong teamwork, communication, and problem-solving skills. Nice to Have: Experience with PyTorch or TensorFlow for AI-based perception or control. Exposure to distributed, embedded, or real-time systems. Knowledge of simulation tools like Gazebo or RViz. Experience with GPU programming (CUDA/OpenCL More ❯

prototype cutting-edge AI techniques (e.g., deep learning, reinforcement learning, generative models). Support continuous model improvement and scalable MLOps deployment pipelines. TECH STACK/REQUIREMENTS Core Skills: Python, TensorFlow/PyTorch, scikit-learn, OpenCV, NumPy, Pandas Experience With: Model training, tuning, and deployment in production environments Preferred: Sports data analytics, time-series forecasting, or computer vision experience Infrastructure … analytics TO BE CONSIDERED... Please apply directly by emailing jordanna.ramsey@searchability.com with your CV and availability. KEYWORDS: AI Engineer, Machine Learning Engineer, Sports Analytics, Computer Vision, Deep Learning, Python, TensorFlow, PyTorch, MLOps, Data Science, Predictive Modelling, Sports Tech, AI in Sports More ❯

equivalent experience in 3D graphics or ML systems. Strong in C Python, 3D graphics pipelines, inverse rendering, and geometry processing. Experience with GPU programming (OpenGL, CUDA, Vulkan), PyTorch/TensorFlow, and real-time engines (Unity/Unreal). Solid grasp of optimization, linear algebra, computer vision, and numerical methods. Skilled in multithreading, memory management, and profiling for high-performance More ❯

small as they want people to have a major say and influence on projects. Technical Skills: Python - strong knowledge required Experience working across a range of ML models, e.g. TensorFlow and scikit-learn Commercial experience working on short-term forecasting markets, across either energy, power or financial markets. GitHub or Azure DevOps knowledge is desired SQL knowledge is desired More ❯

systems (MSc/PhD or equivalent experience). Hands-on experience building or deploying agentic AI or multi-agent systems. Proficiency in Python and modern AI frameworks (e.g. PyTorch, TensorFlow, LangChain, Hugging Face). Familiarity with LLM fine-tuning, reasoning, or retrieval-augmented generation (RAG). Desirable: Experience with AI orchestration, workflow automation, or public-sector technology projects. Knowledge More ❯

ML Engineers Requirements PhD (or equivalent) in Computer Vision, Machine Learning, or related field. Proven record deploying large-scale CV models in production. Strong Python skills with PyTorch or TensorFlow expertise. Deep understanding of modern CV architectures, especially LVMs and Transformers. Experience with multimodal data (images, video, text) and MLOps workflows. Hands-on, self-directed, evidence-driven, and collaborative More ❯

in AI, Machine Learning, Robotics, or related field Proven experience leading AI/ML teams and shipping production solutions Strong in Python , C++ , or Rust , with ML frameworks (PyTorch, TensorFlow, JAX) Background in distributed systems , reinforcement learning , or autonomous agents Collaborative leader who thrives on complex technical challenges What You’ll Do Design and deploy scalable AI-driven systems More ❯

re Looking For Strong hands-on experience with machine learning engineering at scale . Expertise in Python (plus C Java a bonus), and familiarity with ML frameworks like PyTorch, TensorFlow, Scikit-learn . Experience building production-grade pipelines (Spark, Ray, Kafka, Dask, Kubernetes, cloud). Ability to handle large, noisy datasets — financial or otherwise — and turn them into production More ❯

technical subject, ideally including postgraduate study Hands-on experience bringing ML systems from research through to live deployment Strong Python programming skills and experience with libraries such as PyTorch, TensorFlow, or Hugging Face Good understanding of infrastructure and deployment, ideally in cloud environments such as AWS Exposure to areas such as time-series modelling, optimisation, computer vision, or reinforcement More ❯

technical subject, ideally including postgraduate study Hands-on experience bringing ML systems from research through to live deployment Strong Python programming skills and experience with libraries such as PyTorch, TensorFlow, or Hugging Face Good understanding of infrastructure and deployment, ideally in cloud environments such as AWS Exposure to areas such as time-series modelling, optimisation, computer vision, or reinforcement More ❯

development. • Experience with parallel processing programming. • Understanding of standardization processes and standard-developing organizations (SDOs). Beneficial to have: • Knowledge of objective Visual Quality (VQ) assessment techniques. • Experience with TensorFlow, visual AI (e.g., media indexing), and/or multimodal Generative AI. • Experience in Intellectual Property development. • Experience presenting research findings at conferences and within video-centric forums. • Contribution to More ❯

projects from idea → production with measurable impact. Deep hands-on expertise with LLMs (fine-tuning, prompt engineering, evaluation, and deployment at scale). Hands-on experience with PyTorch/TensorFlow, LangChain, vector databases , or similar tools. Excellent communicator; comfortable working with non-technical stakeholders. Thrive in chaos and love building zero-to-one . This isn’t just another More ❯