1 to 25 of 537 Permanent TensorFlow Jobs

or Machine Learning Professional Certification. Familiarity with traditional machine learning tools such as Python, SKLearn, XGBoost, SparkML, etc. Experience with deep learning frameworks like TensorFlow or PyTorch. Knowledge of ML model deployment options (e.g., Azure Functions, FastAPI, Kubernetes) for real-time and batch processing. Experience with CI/CD More ❯

applications. Required Skills & Qualifications Technical Expertise: Minimum of 8 years of work experience with hast 4 years in Python; familiarity with frameworks like PyTorch, TensorFlow, and libraries like Hugging Face Transformers. Hands-on experience with LLMs (e.g., OpenAI GPT models, Anthropic Claude) and fine-tuning techniques. Strong understanding of More ❯

of a wide range of ML algorithms. Understanding of MLOps practices for managing and monitoring models in production. Experience with deep learning frameworks (e.g., TensorFlow, PyTorch). Proficiency in programming languages such as Python, SQL, and R. Knowledge of SQL and NoSQL databases for data storage and retrieval. Experience More ❯

large datasets and with streaming data architectures. Demonstrated knowledge of large language models and generative AI. ML frameworks (Scikit-Learn, NumPy, SciPy, Pandas, XGBoost, Tensorflow, PyTorch, MXNet, LLM) Qualifications Required: Bachelor's Degree with 7 years experience; Master's Degree with 6 years experience; PhD with 2 years experience. More ❯

Learning & Model Development Experience developing and fine-tuning machine learning models, including supervised and unsupervised learning. Applied knowledge of deep learning frameworks such as TensorFlow or PyTorch. Familiarity with transformer-based architectures (e.g., BERT, GPT) and usage of Hugging Face Transformers. Ability to design and implement basic model training More ❯

ML models in a production environment. Proficiency in programming languages such as Python, Java, or C++. Experience with machine learning frameworks and libraries (e.g., TensorFlow, PyTorch, Scikit-learn). Familiarity with data processing tools and platforms (e.g., SQL, Apache Spark, Hadoop). Knowledge of cloud computing services (e.g., AWS More ❯

Programming Languages: Proficiency in Python and experience with languages such as Java or Scala. ? AI Frameworks: Extensive experience with AI frameworks and libraries, including TensorFlow, PyTorch, or similar. ? Data Processing: Expertise in big data technologies such as Apache Spark, Hadoop, and experience with data pipeline tools like Apache Airflow. More ❯

Job Details Education: Bachelor's, Master's, or PhD in Computer Science, AI, Data Science, or a related field. Programming Skills: Proficiency in Python, TensorFlow, PyTorch, Scikit-learn, or similar frameworks. Machine Learning & AI Expertise: Strong knowledge of supervised, unsupervised, and reinforcement learning. Data Handling: Experience with big data 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 ❯

SQL, MongoDB Experience on general programming languages: Python, C++, Java, etc. Experience with deep learning, machine learning and NLP frameworks such as PyTorch (or TensorFlow), HuggingFace Transformer, Scikit-learn Experience with working in Linux A strong intuition for what makes products a joy to use Empathy for how different More ❯

algorithms and NLP techniques, with hands-on experience in either academia or industry. Proficiency in Python and experience with ML/NLP libraries like TensorFlow, PyTorch, scikit-learn, or Hugging Face. Experience working with cloud platforms such as AWS, GCP, or Azure. Familiarity with advanced NLP methods, including Prompt More ❯

and multi-agent systems (MAS). Advanced Python programming skills, with a strong emphasis on writing efficient, scalable, and maintainable code. Proven experience with TensorFlow/PyTorch/Jax, Scikit-learn, and MLOps workflows for training, deployment, and monitoring of ML models. Experience working with Polars and/or More ❯

Artificial Intelligence, or a related field, or equivalent professional experience Strong programming skills in Python, with experience in machine learning frameworks such as PyTorch, TensorFlow or JAX Hands-on experience fine-tuning LLMs and optimising hyperparameters for improved performance Skilled in building LLM-powered applications for real-time decision More ❯

implementation. Contribute to internal initiatives such as blogs & technical forums. Requirements Substantial experience with Python and relevant libraries (e.g. Pandas, Numpy, Scikit Learn, PyTorch, Tensorflow). Experience driving ML & data science solutions into production. You can put the numbers into a business perspective - you're a data storyteller. You More ❯

related field. Proficiency in programming languages such as Python, R, or Java. Strong understanding of mathematics and statistics. Experience with machine learning frameworks like TensorFlow, Keras, or PyTorch. Knowledge of data analysis and visualization tools (e.g., Pandas, NumPy, Matplotlib). Familiarity with big data technologies (e.g., Hadoop, Spark). More ❯

in AI and data-driven architecture design. Extensive experience in enterprise architecture frameworks (e.g., TOGAF, Zachman). Expertise in AI/ML technologies (e.g., TensorFlow, PyTorch, Scikit-learn, Keras) and understanding of deep learning and natural language processing (NLP). Strong understanding of big data platforms such as Hadoop More ❯

with advanced AI leaders. Strong programming skills in languages such as Python, Java, or C++. Experience with AI and machine learning frameworks such as TensorFlow, PyTorch, or scikit-learn. What You'll Bring Preferred qualifications: Experience with cloud platforms such as AWS, Azure, or Google Cloud. Familiarity with data More ❯

PostgreSQL preferred but general SQL knowledge is more important). Familiarity with latest Data Science platforms (e.g. Databricks, Dataiku, AzureML, SageMaker) and frameworks (e.g. Tensorflow, MXNet, scikit-learn). Knowledge of software engineering practices (coding practices to DS, unit testing, version control, code review). Experience with Hadoop (especially More ❯

Proficiency in using JupyterLab or AWS Sagemaker for interactive data analysis and model development. Strong proficiency in Python and experience with libraries such as TensorFlow, PyTorch, Scikit-learn, Pandas, NumPy and Statsmodels. Expertise in time series forecasting techniques, such as RNNs, LSTMs and GRUs. Knowledge of Grafana (or similar More ❯

Accountability: Owns and takes responsibility for the quality and delivery of the assigned tasks Desired skills Machine Learning and Deep Learning Frameworks: Scikit-learn, TensorFlow, PyTorch, Keras etc. Communication: Effectively communicates complex technical concepts to a diverse audience including technical, and non-technical stakeholders, both verbally and in writing More ❯

with training and evaluating BERT-like models in real-world applications, especially in NLP or classification problems. Hands on experience with ML tools like TensorFlow, PyTorch etc. Experience with data science libraries such as NLTK, Scikit-learn, SciPy, (Sci)SpaCy etc. Excellent problem-solving and programming skills in Python More ❯

graph technology and/or algorithms Our technology stack Python and associated ML/DS libraries (Scikit-learn, Numpy, LightlGBM, Pandas, LangChain/LangGraph, TensorFlow, etc ) PySpark AWS cloud infrastructure: EMR, ECS, Athena, etc. MLOps: Terraform, Docker, Airflow, MLFlow More information: Enjoy fantastic perks like private healthcare & dental insurance More ❯

how to fine-tune those models e.g. 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 More ❯

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 More ❯

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 More ❯