151 to 175 of 499 Permanent Keras Jobs

track record in the successful development and deployment of AI/ML-based tools. Strong command over Python and major ML frameworks such as Keras, PyTorch, TensorFlow, or Scikit-Learn. Extensive experience in building and implementing predictive models to design biological sequences and/or analyse biological sequence data (DNA More ❯

track record in the successful development and deployment of AI/ML-based tools. Strong command over Python and major ML frameworks such as Keras, PyTorch, TensorFlow, or Scikit-Learn. Extensive experience in building and implementing predictive models to design biological sequences and/or analyse biological sequence data (DNA More ❯

track record in the successful development and deployment of AI/ML-based tools. Strong command over Python and major ML frameworks such as Keras, PyTorch, TensorFlow, or Scikit-Learn. Extensive experience in building and implementing predictive models to design biological sequences and/or analyse biological sequence data (DNA More ❯

track record in the successful development and deployment of AI/ML-based tools. Strong command over Python and major ML frameworks such as Keras, PyTorch, TensorFlow, or Scikit-Learn. Extensive experience in building and implementing predictive models to design biological sequences and/or analyse biological sequence data (DNA More ❯

track record in the successful development and deployment of AI/ML-based tools. Strong command over Python and major ML frameworks such as Keras, PyTorch, TensorFlow, or Scikit-Learn. Extensive experience in building and implementing predictive models to design biological sequences and/or analyse biological sequence data (DNA More ❯

track record in the successful development and deployment of AI/ML-based tools. Strong command over Python and major ML frameworks such as Keras, PyTorch, TensorFlow, or Scikit-Learn. Extensive experience in building and implementing predictive models to design biological sequences and/or analyse biological sequence data (DNA 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 ❯

in data science or building LLM applications, especially in the cybersecurity domain. Strong practical experience in Python and tools like Scikit-Learn, TensorFlow, PyTorch, Keras, Pandas, Polars, Spark, and DuckDB . Demonstrated experience applying LLMs to cybersecurity or other high-complexity, domain-specific problems. Understanding of network and cloud security More ❯

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 More ❯

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 ❯

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 ❯

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 ❯

/Kubernetes).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 of our 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 ❯

. 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 ❯

. 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 ❯