51 to 75 of 3,178 Permanent TensorFlow Jobs

to computational linguistics is highly desirable, from both academic research and commercial perspectives. Proficiency in Python and ML libraries such as Hugging Face, PyTorch, TensorFlow, and Scikit-learn. Experience deploying AI solutions into production environments using AWS, GCP, or Azure. Hands-on experience with MLOps, CI/CD for More ❯

years leading AI/ML teams or initiatives in cross-functional settings Strong proficiency in Python and ML/DL frameworks such as PyTorch, TensorFlow, Transformers, and LangChain Experience with cloud platforms (Azure or AWS) and MLOps practices (Docker, Kubernetes, CI/CD) Demonstrated ability to deliver scalable AI More ❯

years leading AI/ML teams or initiatives in cross-functional settings Strong proficiency in Python and ML/DL frameworks such as PyTorch, TensorFlow, Transformers, and LangChain Experience with cloud platforms (Azure or AWS) and MLOps practices (Docker, Kubernetes, CI/CD) Demonstrated ability to deliver scalable AI More ❯

learn and adapt to new tools and technologies. Preferred Qualifications (Nice-to-Have): Basic understanding of machine learning concepts and frameworks like Scikit-learn, TensorFlow, or PyTorch. Understanding of DevOps practices and CI/CD pipelines. Familiarity with cloud services such as AWS, Azure, or GCP. Hands-on experience More ❯

S3, Athena, Glue). Strong problem-solving and teamwork skills. Leadership and mentorship abilities. Highly Desirable Skills Experience with deep learning libraries (Keras, PyTorch, TensorFlow). Knowledge of data processing tools (Pyspark, Hive) and databases (MongoDB, SQL, NoSQL). NLP expertise (nltk, SpaCy), especially with unstructured financial data. Understanding More ❯

learn and adapt to new tools and technologies. Preferred Qualifications (Nice-to-Have): Basic understanding of machine learning concepts and frameworks like Scikit-learn, TensorFlow, or PyTorch . Understanding of DevOps practices and CI/CD pipelines. Familiarity with cloud services such as AWS, Azure, or GCP. Hands-on More ❯

Terraform code & MLOps practices. Exhibit proficiency in Python, software engineering practices, along with expertise in deep learning frameworks (ML/distributed ML frameworks like TensorFlow etc). Possess outstanding communication skills and the ability to collaborate effectively with interdisciplinary teams. Proven experience in the full ML model development lifecycle More ❯

learn and adapt to new tools and technologies. Preferred Qualifications (Nice-to-Have) Basic understanding of machine learning concepts and frameworks like Scikit-learn, TensorFlow, or PyTorch . Understanding of DevOps practices and CI/CD pipelines. Familiarity with cloud services such as AWS, Azure, or GCP. Hands-on More ❯

for you if: Python for API and Model development (Machine learning frameworks and tooling e.g. Sklearn) and (Deep learning frameworks such as Pytorch and Tensorflow) Understanding of machine learning techniques Experience with data manipulation libraries (e.g. Pandas, Spark, SQL) Problem solving skills Git for version control Cloud experience (we More ❯

source control, CI/CD for models, model registries, etc.) on Azure or similar platforms. Proficiency in Python and common ML frameworks (scikit-learn, TensorFlow/PyTorch) and experience with code review and DevOps processes. Leadership & Communication: Excellent leadership and interpersonal skills. Able to interface with client stakeholders to More ❯

source control, CI/CD for models, model registries, etc.) on Azure or similar platforms. Proficiency in Python and common ML frameworks (scikit-learn, TensorFlow/PyTorch) and experience with code review and DevOps processes. Leadership & Communication: Excellent leadership and interpersonal skills. Able to interface with client stakeholders to More ❯

source control, CI/CD for models, model registries, etc.) on Azure or similar platforms. Proficiency in Python and common ML frameworks (scikit-learn, TensorFlow/PyTorch) and experience with code review and DevOps processes. Leadership & Communication: Excellent leadership and interpersonal skills. Able to interface with client stakeholders to More ❯

end-to-end ML pipelines Hand-on experience in Python data science ecosystem (e.g. numpy, scipy, pandas, scikit-learn, matplotlib etc.) Deep Learning frameworks (TensorFlow, PyTorch, MLX) Popular classification and regression techniques Unsupervised learning & matrix factorisation algorithms Natural Language Processing (NLP) and document processing Generative AI (open and closed More ❯

applications, particularly in fraud prevention and user personalization. Experience designing, developing, and implementing advanced machine learning models. Familiarity with machine learning frameworks such as TensorFlow, PyTorch, and scikit-learn. Data Engineering Skills: Proficiency in developing and maintaining real-time data pipelines for processing large-scale data. Experience with ETL More ❯

modalities such as computational pathology, genomics, transcriptomics or medical imaging. Strong experience with Python and at least one deep learning frameworks such as PyTorch, TensorFlow, JAX, and PyTorch Lightning. Familiarity with packages and technologies such as NumPy, Pandas, Scikit-learn, Scikit-image, OpenCV, Git, and Bash. Experience working with More ❯

AI (XAI) methods for clinical and biological interpretability. Strong experience with Python and at least one deep learning framework such as PyTorch, PyTorch Lightning, TensorFlow or JAX. Familiarity with packages and technologies such as NumPy, Pandas, Scikit-learn, Scikit-image, OpenCV, Git, and Bash. Experience in developing and finetuning More ❯

in developing and deploying machine learning models, with a strong focus on generative AI techniques. - Proficiency in programming languages such as Python, PyTorch, or TensorFlow, and experience with deep learning frameworks. - Strong background in natural language processing, computer vision, or multimodal learning. - Ability to communicate technical concepts to both More ❯

potential application within our business. About you: DATA SCIENCE • Extensive proficiency in Python and its associated data science libraries (e.g., Pandas, NumPy, scikit-learn, TensorFlow, PyTorch) and data visualisation libraries (e.g., Plotly, Dash). • Strong knowledge and practical application of statistical analysis and data visualization techniques. • Strong experience of More ❯

data-driven tactical and strategic analytics and insights using ML, NLP, computer vision solutions. Demonstrated 1+ years hands-on experience with Python, Hugging Face, TensorFlow, Keras, PyTorch, Spark or similar statistical tools. Expert in python programming. 1+ years hands-on experience developing natural language processing (NLP) models, ideally with More ❯

presenting work to clients and managing stakeholder relationships. Experience with data science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g., Keras, TensorFlow, PyTorch, scikit-learn). Experience deploying solutions on Cloud platforms (AWS, Azure, Google Cloud) including provisioning tools like Terraform. Proven skills in deploying technologies More ❯

in RFI/RFP processes, preparing bids, and delivering presentations. Familiarity with data science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g., Keras, TensorFlow, PyTorch, scikit-learn). Experience deploying solutions on Cloud platforms (AWS, Azure, Google Cloud) using provisioning tools like Terraform. Proven ability to deploy technologies More ❯

sector clients through RFI/RFP processes, bids, and presentations. Familiarity with data science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g., Keras, TensorFlow, PyTorch, scikit-learn). Cloud experience in deploying solutions on AWS, Azure, or Google Cloud, including provisioning tools like Terraform. Experience with deployment technologies More ❯

public sector clients through RFI/RFP, bids, and presentations. Familiarity with data science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g., Keras, TensorFlow, PyTorch, scikit-learn). Cloud experience with AWS, Azure, Google Cloud, including provisioning tools like Terraform. Deployment experience using Docker, Kubernetes, CI/CD More ❯

sector clients, including RFI/RFP processes, bids, and presentations. Familiarity with data science platforms (e.g., Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g., Keras, TensorFlow, PyTorch, scikit-learn). Experience deploying solutions to Cloud platforms (AWS, Azure, Google Cloud) and using Cloud provisioning tools like Terraform. Proven ability to More ❯

bidder, documented bids and face to face presentations. Experience of data science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and machine learning frameworks (e.g. Keras, Tensorflow, PyTorch, scikit-learn) Cloud platforms – demonstrable experience of building and deploying solutions to Cloud (e.g. AWS, Azure, Google Cloud) including Cloud provisioning tools (e.g. More ❯