26 to 45 of 45 TensorFlow Jobs in Berkshire

Data Scientist/Data Engineer A understand of Palantir would be a huge + Experience of completing projects to deadline. Experience in Deep Learning and DL frameworks such as Tensorflow/Pytroch Deploying ML models Good command of Python and use of libraries for data science – scikit-learn, NumPy, matplotlib Relation database experience with data manipulation skills in SQL 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 ❯

Have: Previous experience as a Data Scientist or Data Engineer Strong command of Python (including libraries such as scikit-learn, NumPy, matplotlib) Experience in deep learning frameworks such as TensorFlow or PyTorch Knowledge of SQL and relational databases; experience with Big Data environments Familiarity with API development and NoSQL databases Understanding of CI/CD practices , AWS , and GIT 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 ❯

deployment hurdles. Ability to translate business questions into analytical frameworks and interpret results for non-technical stakeholders. Strong proficiency in Python, SQL, and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch). Experience with model operationalization using tools like Docker, Kubernetes, MLflow, or SageMaker. Marketing KPIs knowledge: CTR, conversion rate, MQL to SQL, ROI, CLV, CAC, retention. Experience working … Prophet, or custom implementations for time series A/B testing frameworks (e.g., DoWhy, causalml) Programming & Data Tools : Python: Strong foundation in Pandas, NumPy, matplotlib/seaborn, scikit-learn, TensorFlow, Pytorch etc. SQL: Advanced querying for large-scale datasets. Jupyter, Databricks, or notebooks-based workflows for experimentation. Data Access & Engineering Collaboration : Comfort working with cloud data warehouses (e.g., Snowflake 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 ❯

highly preferred Demonstrated ability to deploy production-level ML models—particularly in optimisation, demand forecasting, or computer vision Advanced proficiency in Python and ML frameworks such as Scikit-learn, TensorFlow, or PyTorch Solid understanding of supervised and unsupervised learning, statistical modelling, and mathematical optimisation Hands-on experience with AWS services, especially SageMaker, Lambda, and related infrastructure Willingness to contribute 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 ❯

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 ❯

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 ❯

About Us At Aspect, we’re one of London’s largest property maintenance teams, covering more trades than anyone else and operating 24/7. After more than 15 years of trusted service to thousands of residential and commercial customers More ❯

and RAG patterns. Design and build robust data and ingestion pipelines, integrate vector databases, and RSG. Expert-level proficiency in Python and key ML libraries (Langchain, Semantic Kernel, PyTorch, TensorFlow). Hands-on experience with cloud platforms (Azure, AWS) and infrastructure-as-code (Terraform, ECS). Strong background in deploying models via APIs, containers, or cloud-native services. Proven … Minimum 7 years’ professional experience in AI, ML, or applied machine learning engineering roles. Required Skills Expert-level proficiency in Python and key ML libraries (Langchain, Semantic Kernel, PyTorch, TensorFlow). Hands-on experience with cloud platforms (Azure, AWS) and infrastructure-as-code (Terraform, ECS). Strong background in deploying models via APIs, containers, or cloud-native services. Proven More ❯