51 to 75 of 241 Keras Jobs

Learning, Deep Learning, or Natural Language Processing.Some hands-on experience with AI concepts, libraries, or frameworks (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers, Keras, etc.) Familiarity with Python for AI/ML development is a significant advantage. Experience with data engineering pipelines or big data technologies (e.g., Kafka, Spark More ❯

techniques Able to apply machine learning to real-life problems Vision Transformers, DeepLabv3, SegFormer, etc.Python, Scikit-Learn, NumPy, Pandas and PyTorch/TensorFlow/Keras Thrive in a cross-functional working environment Possess a clear passion for data science beyond the day job Nice-to-haves: On offer : Base salary More ❯

techniques Able to apply machine learning to real-life problems Vision Transformers, DeepLabv3, SegFormer, etc.Python, Scikit-Learn, NumPy, Pandas and PyTorch/TensorFlow/Keras Thrive in a cross-functional working environment Possess a clear passion for data science beyond the day job Nice-to-haves: On offer : Base salary More ❯

industry experience. Strong proficiency in programming languages such as Python, C++, or similar. Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Keras, or OpenCV. Proven ability to develop and optimise deep learning models for image and video analysis. Understanding of medical imaging and video data is advantageous. More ❯

and TDD. Excellent teamwork and collaboration skills. Preferred but not mandatory: Experience with Databricks and PySpark. Experience with deep learning frameworks such as TensorFlow, Keras, or PyTorch. Data science experience in E-commerce or retail sectors. Proficiency in English, both written and spoken. About Pandora: Founded in , Pandora designs, manufactures More ❯

Machine learning and deep learning concepts• Skilled in python frameworks such as scikit-learn, scipy, numpy etc and DL libraries such as tensor flow, keras• Skilled in GenAI Projects such as text Summarization, chatbot creation using LLM models GPT4, Med-Palm, LLAMA etc.• Skilled in fine tuning open source LLM More ❯

Master's in the above subjects with 3-4 years of industrial experience in a relevant competitive environment. Proficiency in Python, Dask, Numpy, Pandas, Keras and PyTorch. Experience withsingle-cell sequencing data Passion for knowledge sharing, mentoring colleagues, and shaping scientific strategy as part of a growingleadership team. What We More ❯

e.g. spaCy, NumPy, SciPy, Transformers, etc.), data tools and technologies (Spark, Hadoop, Hive, Redshift, SQL), and toolkits for ML and deep learning (SparkML, Tensorflow, Keras). Demonstrated ability to work on multi-disciplinary teams with diverse skillsets. Deploying machine learning models and systems to production (DevOps, MLOps, CI/CD More ❯

different levels across the organization. Demonstrated technical documentation skill is a must. Fluent in written and oral English. Familiarity with machine learning frameworks (like Keras or PyTorch) and libraries (e.g., scikit-learn),experience in designing machine learning and AI applications to effectively optimize business processes and support better decision-making More ❯

Deep Learning, or Natural Language Processing. Some hands-on experience with AI concepts, libraries, or frameworks (e.g., TensorFlow, PyTorch, scikit-learn, Hugging Face Transformers, Keras, etc.). Familiarity with Python for AI/ML development is a significant advantage. Experience with data engineering pipelines or big data technologies (e.g., Kafka More ❯

. we'd also encourage you to apply if you possess: Experience with Spark/Databricks. Experience deploying ML models via APIs (e.g., Flask, Keras). Startup experience or familiarity with geospatial and financial data. The Interview Process (subject to change): You’ll start with an introductory call with one More ❯

. we'd also encourage you to apply if you possess: Experience with Spark/Databricks. Experience deploying ML models via APIs (e.g., Flask, Keras). Startup experience or familiarity with geospatial and financial data. The Interview Process (subject to change): You’ll start with an introductory call with one More ❯

. we'd also encourage you to apply if you possess: Experience with Spark/Databricks. Experience deploying ML models via APIs (e.g., Flask, Keras). Startup experience or familiarity with geospatial and financial data. The Interview Process (subject to change): You’ll start with an introductory call with one More ❯

RELOCATION ASSISTANCE: No relocation assistance available CLEARANCE TYPE: Secret TRAVEL: Yes, 10% of the Time Description At Northrop Grumman, our employees have incredible opportunities to work on revolutionary systems that impact people's lives around the world today, and for More ❯

Direct message the job poster from Dabster At Dabster, we specialize in connecting top talent with leading global companies. We are currently seeking an experienced Gen AI Architect to join our client's team in London, UK . Our mission More ❯

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 More ❯

methods using both quantitative and qualitative metrics. Strong mathematical and statistical background. Deep knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow, and PySpark. Experience and understanding of mixed technical teams such as engineering, architects, business analysts. Familiar with MLOps industry best practices. Good stakeholder More ❯

least 1 year in a leadership role. Strong knowledge of Machine Learning. Advanced knowledge of Python & DS packages (numpy/pandas/sklearn/keras, etc.); ability to optimize and speed up code. Solid experience with SQL (MySQL, Google BigQuery); understanding of data warehousing and ETL processes. Know how to More ❯

on ML development Qualifications Master's degree or PhD in computer science, statistics, math, physics, or similar through experience Experience with Python (TensorFlow/Keras/sklearn/PyTorch/) Previous experience in delivering ML projects High standards, disciplined, good communicator and team player Wanting to take ownership What we More ❯

methods using both quantitative and qualitative metrics. Strong mathematical and statistical background. Deep knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow, and PySpark. Experience and understanding of mixed technical teams such as engineering, architects, business analysts. Familiar with MLOps industry best practices. Good stakeholder More ❯

methods using both quantitative and qualitative metrics. Strong mathematical and statistical background. Deep knowledge of Python and data science packages such as Scikit learn, Keras, Tensor flow, and PySpark. Experience and understanding of mixed technical teams such as engineering, architects, business analysts. Familiar with MLOps industry best practices. Good stakeholder More ❯

including data structures, algorithms, system design, and OOP. You have advanced knowledge of LLM architectures and ML/DL frameworks (e.g., TensorFlow, PyTorch, LangChain, Keras, scikit-learn). You're ready to design, deploy, and maintain production-grade Machine Learning systems. You're willing to champion best practices in code More ❯

focus on Data Science/Artificial Intelligence/Text Mining/Natural Language Processing. Experience with machine learning and deep learning frameworks such as Keras, TensorFlow, and scikit-learn. Proficiency in knowledge graph frameworks and tools, including Neo4j, GraphQL, RDFLib, or similar technologies, is essential. Strong programming skills and experience More ❯

or similar tools used in large-scale data processing Exposure to machine learning model deployment using APIs or lightweight serving frameworks like Flask or Keras Familiarity with geospatial data would be a great bonus! If this role interests you and you would like to learn more, please apply here or More ❯

or similar tools used in large-scale data processing Exposure to machine learning model deployment using APIs or lightweight serving frameworks like Flask or Keras Familiarity with geospatial data would be a great bonus! If this role interests you and you would like to learn more, please apply here or More ❯