1 to 25 of 33 Permanent Keras Jobs

experience in developing and deploying machine learning models in a production environment. Strong programming skills in Python and experience with relevant machine learning libraries and frameworks such as TensorFlow, Keras, PyTorch, scikit-learn, etc. Solid understanding of machine learning algorithms (e.g., regression, classification, clusting, dimensionality reduction, deep learning architectures). Experience with data preprocessing, feature engineering, and data visualization techniques. More ❯

3+ years of demonstrated and related industry experience Strong programming skills in languages such as Python, Java, and/or R. Experience with machine learning frameworks such as TensorFlow, Keras, and/or PyTorch. Solid understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning), deep learning, and neural networks. Experience with data preprocessing, feature engineering, and model evaluation techniques.\Familiarity More ❯

scale distributed systems, edge computing and cloud systems (AWS, Azure), e.g., microservices, event-streaming/messaging, container orchestration (Docker, Kubernetes), DevOps Experience building applications using deep learning frameworks like Keras, Tensorflow, PyTorch in either production or research settings Has experience with the machine learning product lifecycle as well as runtime integration and performance optimization Knowledge in Siemens Software solutions (e.g. More ❯

security standards and proactively reporting risks and incidents to protect against cyber threats and data loss. You have: Proficiency in machine learning and deep learning frameworks such as TensorFlow, Keras, and PyTorch, with strong programming skills in Python (Pandas, NumPy, PySpark, Jupyter) and experience using Git for version control. A degree in Mathematics, Physics, Computer Science, Engineering, or a related More ❯

security standards and proactively reporting risks and incidents to protect against cyber threats and data loss. You have: Proficiency in machine learning and deep learning frameworks such as TensorFlow, Keras, and PyTorch, with strong programming skills in Python (Pandas, NumPy, PySpark, Jupyter) and experience using Git for version control. A degree in Mathematics, Physics, Computer Science, Engineering, or a related More ❯

Previous experience developing underwriting or behavioural models for credit extension Desired: Master's degree in data science/Machine Learning or related discipline Knowledge of Deep Learning frameworks, ideally Keras/Tensorflow Familiarity with software version control (GitHub, bitbucket) Knowledge of Tableau Ability to comprehend research papers and possibly apply their solutions Credit card industry knowledge What's in it More ❯

Previous experience developing underwriting or behavioural models for credit extension Desired: Master's degree in Data Science/Machine Learning or related discipline Knowledge of Deep Learning frameworks, ideally Keras/Tensorflow Familiarity with software version control (GitHub, bitbucket) Knowledge of Tableau Ability to comprehend research papers and possibly apply their solutions Credit card industry knowledge What's in it More ❯

in machine learning, computer science, engineering, or a related discipline, with a BSc required and an MSc considered advantageous. Experienced in using machine learning frameworks such as Scikit-learn, Keras, and PyTorch, with additional familiarity with MLFlow and AzureML seen as a positive. Have working knowledge of CI/CD practices, ML Ops, ML pipelines, automated testing, and platforms such More ❯

and familiarity with cloud platforms like Amazon Web Services (AWS), Google Cloud Platform (GCP), and Microsoft Azure. Technical Skills Good to have: Expertise in any one framework (TensorFlow, Pytorch, Keras) Experience in a statistical programming language (e.g. R or Python) and applied machine learning and AI techniques (i.e computer vision, deep learning, conversational AI, and natural language processing frameworks.) Experience More ❯

modelling techniques and how to fine-tune those models eg. XGBoost, Deep Neural Networks, Transformers, ResNets, VAEs, GANs, Markov chains, etc. Experience using specialized machine learning libraries eg. 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 they emerge. Experience of using More ❯

roles. Strong expertise in Machine Learning and Deep Learning, with exposure to Reinforcement Learning as a plus. Proficiency in Python and modern ML libraries (e.g., TensorFlow, PyTorch, JAX, or Keras). Experience with version control systems (GitHub, GitLab) and knowledge of clean, maintainable coding practices. Familiarity with CI/CD pipelines for automating ML workflows. Ability to thrive in a More ❯

science, engineering, or computer science - Experience communicating across technical and non-technical audiences - Experience in using Python and hands on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet - Fluency in written and spoken English Amazon is an equal opportunities employer. We believe passionately that employing a diverse workforce is central to our success. We make recruiting More ❯

skills; ideas need to land Bachelor's degree in computer science, Mathematics, Statistics, or related field Bonus points for Credit card or consumer finance experience Exposure to deep learning (Keras, TensorFlow) Git, Tableau, Bitbucket Master's in Data Science or similar What's on offer Up to £75k depending on experience Bonus scheme + private medical 2530 days holiday + More ❯

skills; ideas need to land Bachelor's degree in computer science, Mathematics, Statistics, or related field Bonus points for Credit card or consumer finance experience Exposure to deep learning (Keras, TensorFlow) Git, Tableau, Bitbucket Master’s in Data Science or similar What’s on offer Up to £75k depending on experience Bonus scheme + private medical 25–30 days holiday More ❯

skills; ideas need to land Bachelor's degree in computer science, Mathematics, Statistics, or related field Bonus points for Credit card or consumer finance experience Exposure to deep learning (Keras, TensorFlow) Git, Tableau, Bitbucket Master’s in Data Science or similar What’s on offer Up to £75k depending on experience Bonus scheme + private medical 25–30 days holiday More ❯

embedded or cloud software (python, C/C++, or equivalent) with exposure to Linux or RTOSs. • Experience with data analysis & machine learning, including Python ML & data libraries (e.g. TensorFlow, Keras, PyTorch, NumPy, Pandas, or equivalent). • Experience developing, launching, or maintaining technical products in relevant commercial industries (e.g. industrial, medical, automotive, IoT, or related markets). • Track record of teaming More ❯

learning, and data science, with a strong focus on foundation models and large language models Masterful proficiency in Python and expertise in AI frameworks such as TensorFlow, PyTorch, or Keras Deep understanding of cloud platforms (AWS, Azure, GCP) and related services Proven track record of delivering complex AI solutions in a professional setting Experience of working with Generative AI models More ❯

proof of concepts of new technologies and evaluating the state of the art in machine learning algorithms for text analytics Demonstrated experience with machine learning frameworks such as PyTorch, Keras, Tensorflow Demonstrated experience with data visualization tools (i.e. Tableau, Pandas, D3.js, ggplot, etc) Demonstrated experience with NoSQL data stores such as MongoDB or DynamoDB Demonstrated experience using Natural Language Processing More ❯

foundation in statistical analysis and proven experience applying a range of machine learning techniques to solve business problems (e.g., regression, classification, clustering, time-series forecasting). Practical experience with Keras or PyTorch is required. Full-Stack Deployment: Demonstrable experience taking models to production, including building and deploying APIs with FastAPI and using Vertex AI for ML workflows. Visualization & Communication: Ability More ❯

performance computing, neural deep learning methods and/or machine learning PREFERRED QUALIFICATIONS Experience in using Python and hands on experience building models with deep learning frameworks like Tensorflow, Keras, PyTorch, MXNet - Prior experience in training and fine-tuning of Large Language Models (LLMs) - Knowledge of AWS platform and tools Our inclusive culture empowers Amazonians to deliver the best results More ❯

of machine learning modelling techniques and 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 they emerge. Experience of using More ❯

skills, a quick learning ability, and enthusiasm for tackling complex challenges. You are proficient in Python, with experience using PySpark and ML libraries such as scikit-learn, TensorFlow, or Keras . You are familiar with big data technologies (e.g., Hadoop, Spark), cloud platforms (AWS, GCP), and can effectively communicate technical concepts to non-technical stakeholders. Accommodation requests If you need More ❯

is essential as you'll be the domain expert from day one. Excellent Python programming skills and strong familiarity with ML libraries such as scikit-learn, XGBoost, TensorFlow, PyTorch, Keras etc. Proven track record deploying ML models to production (API, batch, or streaming contexts) Solid understanding of the modern software engineering, infrastructure and data technologies Experience working with LLMs, embeddings More ❯

pain for extreme long-term pain. Embrace an extreme learning rate rather than assuming limits to your ability/knowledge. Responsibilities: Lower deep learning graphsfrom common frameworks (PyTorch, TensorFlow, Keras, etc.) down to an IR representation for trainingwith particular focus on ensuring reproducibility. Write novel algorithms for transforming intermediate representations of compute graphs between different operator representations. Ownership of two More ❯

for extreme long-term pain. Embrace an extreme learning rate rather than assuming limits to your ability/knowledge. Responsibilities: Lower deep learning graphs-from common frameworks (PyTorch, TensorFlow, Keras, etc.) down to an IR representation for training-with particular focus on ensuring reproducibility. Write novel algorithms for transforming intermediate representations of compute graphs between different operator representations. Ownership of More ❯