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Experience with TensorFlow, PyTorch and other common AI Frameworks and Libraries. Understanding AI/ML backend development processes, orchestration of Machine learning models and commonly used DevOps processes for model deployment.
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Experience with Agile methodologies (Scrum, Kanban) and project management tools such as Jira or Azure DevOps. Experience with machine learning frameworks such as TensorFlow, PyTorch, or Keras.
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Experience with Azure DevOps. Familiarity with popular machine learning libraries and frameworks, including TensorFlow, Keras, etc. Experience with Azure DevOps. Familiarity with popular machine learning libraries and frameworks, including TensorFlow, Keras, etc.
Full-timeExpandApply NowActive JobUpdated 7 days ago - UpvoteDownvoteShare Job
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Demonstrated strength in using: Python, Databricks, Azure ML, Azure Cognitive Service, SAS, R, SQL, PySpark, Numpy, Pandas, Scikit Learn, TensorFlow, PyTorch, AutoTS, Prophet, NLTK. Experience with Azure Cloud technologies including Azure DevOps, Azure Synapse, MLOps, GitHub.
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Deep understanding of AI/ML to enhance pipeline efficiency, with experience in TensorFlow, PyTorch, AutoML, Python/R, and MLOps platforms like MLflow and Kubeflow. Solid background in DevOps , including CI/CD automation with Bitbucket Pipelines, Azure DevOps, and GitHub.
ExpandApply NowActive JobUpdated 8 days ago - UpvoteDownvoteShare Job
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Development experience with AI frameworks such as TensorFlow, Microsoft CNTK, scikit, Keras, Caffe, Gluon, Torch. Proven ability to integrate with data engineering platforms and utilize/build modern DevOps/MLOps processes.
ExpandApply NowActive JobUpdated 5 days ago - UpvoteDownvoteShare Job
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Experience with Agile Software Development Lifecycles and DevOps/DevSecOps. Experience with one or more general purpose programming languages including but not limited to: Python, R, Scala, Spark.
Full-timeExpandApply NowActive JobUpdated 1 month ago - UpvoteDownvoteShare Job
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Familiarity with machine learning frameworks (e.g., TensorFlow, PyTorch) and libraries (e.g., scikit-learn). ○ Knowledge of DevOps principles and tools (e.g., CI/CD pipelines, Terraform.
ExpandApply NowActive JobUpdated 14 days ago - UpvoteDownvoteShare Job
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Proficiency in programming languages such as Python, and experience with relevant libraries and tools ( e.g., TensorFlow, PyTorch, scikit-learn ). Collaboration: Collaborate with data scientists, software engineers, and DevOps teams to design and implement robust deployment pipelines for continuous improvement of machine learning models.
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Apexon brings together distinct core competencies – in AI, analytics, app development, cloud, commerce, CX, data, DevOps, IoT, mobile, quality engineering and UX, and our deep expertise in BFSI, healthcare, and life sciences – to help businesses capitalize on the unlimited opportunities digital offers.
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Experience in working with TensorRT, PyTorch, TensorFlow, ONNX Runtime or other ML frameworks. Collaborate with teams of deep learning experts, GPU architects and DevOps engineers across diverse teams.
ExpandApply NowActive JobUpdated 13 days ago - UpvoteDownvoteShare Job
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5+ years of work-related experience in Deep Learning and Machine Learning, including deep learning frameworks TensorFlow or PyTorch, GPU, and CUDA experience extremely helpful. Knowledge of LLM, MLOps, DevOps, and Cloud-oriented workflows using Docker/containers, Kubernetes, cloud APIs, data center deployments, etc.
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Experience with CI/CD and DevOps tools and processes (Azure DevOps, Kustomize, Terraform in particular). Experience with machine learning, large language models, and related tools (e.g. TensorFlow, GPT-3+, LangChain, etc.
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Experience in an Agile working environment and at least one related project management tool (Azure DevOps, Jira, etc.) Extensive experience using common machine learning and deep learning frameworks such as TensorFlow, PyTorch, OpenAI, and LangChain.
$113,100 - $232,300 a yearFull-timeExpandApply NowActive JobUpdated 3 months ago - UpvoteDownvoteShare Job
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Experience with data and data science frameworks such as numpy, pandas, sklearn, nltk, statsmodels, OpenCV, XGBoost, PyTorch, Tensorflow, Keras, etc. Familiarity with software engineering best practices around version control (e.g. Git, Azure DevOps), testing (e.g. PyTest, unittest), containerization (e.g. Docker), and experiment tracking (e.g. MLFlow.
Full-timeExpandApply NowActive JobUpdated 12 days ago
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