1 to 25 of 207 Google TensorFlow Jobs

on experience in developing and deploying machine learning models in a production environment. Strong programming skills in Python and experience with relevant machine learning libraries and frameworks such as TensorFlow, Keras, PyTorch, scikit-learn, etc. Solid understanding of machine learning algorithms (e.g., regression, classification, clusting, dimensionality reduction, deep learning architectures). Experience with data preprocessing, feature engineering, and data More ❯

to our use cases. Required Qualifications Experience in machine learning engineering or applied data science roles. Strong programming skills in Python and experience with ML libraries such as PyTorch, TensorFlow, or Scikit-learn. Deep understanding of machine learning algorithms, statistical modelling, and data structures, with a focus on practical application and performance trade-offs. Experience with cloud platforms (e.g. More ❯

degree in a STEM field: Statistics, Mathematics, Computer Science, Engineering, or similar. Programming proficiency: Strong experience with Python and SQL; familiarity with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Machine learning expertise: Hands-on experience in supervised and unsupervised learning, with exposure to NLP, computer vision, or deep learning a plus. Data visualisation: Proficiency in Tableau More ❯

degree in a STEM field: Statistics, Mathematics, Computer Science, Engineering, or similar. Programming proficiency: Strong experience with Python and SQL; familiarity with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Machine learning expertise: Hands-on experience in supervised and unsupervised learning, with exposure to NLP, computer vision, or deep learning a plus. Data visualisation: Proficiency in Tableau More ❯

degree in a STEM field: Statistics, Mathematics, Computer Science, Engineering, or similar. Programming proficiency: Strong experience with Python and SQL; familiarity with libraries such as Pandas, NumPy, Scikit-learn, TensorFlow, or PyTorch. Machine learning expertise: Hands-on experience in supervised and unsupervised learning, with exposure to NLP, computer vision, or deep learning a plus. Data visualisation: Proficiency in Tableau More ❯

with 3+ years of demonstrated and related industry experience Strong programming skills in languages such as Python, Java, and/or R. Experience with machine learning frameworks such as TensorFlow, Keras, and/or PyTorch. Solid understanding of machine learning algorithms (supervised, unsupervised, reinforcement learning), deep learning, and neural networks. Experience with data preprocessing, feature engineering, and model evaluation More ❯

with a strong portfolio of high-impact projects in production Expert-level programming skills in Python and SQL, and fluency with leading ML/AI frameworks (e.g., scikit-learn, TensorFlow, PyTorch) Direct experience with GenAI/LLM technologies, including tools like Hugging Face, LangChain, OpenAI APIs, vector databases, and fine-tuning methods Deep knowledge of machine learning algorithms (supervised More ❯

Machine Learning. Familiarity with Azure Databricks is a plus. Solid background in machine learning algorithms, data pre-processing, feature engineering, and model evaluation. Experience with deep learning frameworks like TensorFlow or PyTorch is desirable. Proficiency in handling large datasets, experience with Azure Data Factory, Azure SQL Database, and Cosmos DB. Understanding of CI/CD pipelines, containerization (Docker, Kubernetes More ❯

machine learning modelling techniques and 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 they emerge. Experience of using More ❯

Northern Virginia with occasional travel to client sites. A degree in Computer Science or a related field. 3+ years of hands-on experience with Python coding (pandas, numpy, sklearn, TensorFlow, PyTorch, etc.). Proven experience deploying machine learning models into production environments. Proficiency with SQL/NoSQL databases, version control tools (e.g., Git), Docker, and Kubernetes. Strong ownership, accountability More ❯

up to date with the latest advancements in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps More ❯

up to date with the latest advancements in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps More ❯

Stay up-to-date with the latest ML research and tools. Required Skills & Experience Strong proficiency in Python and its ML/data libraries (e.g., NumPy, pandas, scikit-learn, TensorFlow or PyTorch). Hands-on experience with Amazon SageMaker , including training, tuning, and deploying models. Solid understanding of machine learning algorithms and statistical methods. Experience with cloud platforms (AWS More ❯

up to date with the latest advancements in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps More ❯

up to date with the latest advancements in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps More ❯

up to date with the latest advancements in deep learning, computer vision, and related technologies. Key Skills & Experience Strong hands on experience with Computer Vision frameworks (e.g., OpenCV, PyTorch, TensorFlow). Proficiency in Python and ML/DL libraries (NumPy, Pandas, scikit-learn). Proven track record of building and deploying ML models in production environments. Knowledge of MLOps More ❯

and techniques (supervised, unsupervised, reinforcement learning). Solid background in data preprocessing, wrangling, and feature engineering. Proficiency in Python (essential) and familiarity with relevant libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Experience with prompt engineering and model evaluation. Deployment experience using Docker or other containerisation tools. Exposure to GPU-based environments for large-scale model training and tuning. More ❯

and techniques (supervised, unsupervised, reinforcement learning). Solid background in data preprocessing, wrangling, and feature engineering. Proficiency in Python (essential) and familiarity with relevant libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Experience with prompt engineering and model evaluation. Deployment experience using Docker or other containerisation tools. Exposure to GPU-based environments for large-scale model training and tuning. More ❯

and techniques (supervised, unsupervised, reinforcement learning). Solid background in data preprocessing, wrangling, and feature engineering. Proficiency in Python (essential) and familiarity with relevant libraries (NumPy, pandas, scikit-learn, TensorFlow, PyTorch). Experience with prompt engineering and model evaluation. Deployment experience using Docker or other containerisation tools. Exposure to GPU-based environments for large-scale model training and tuning. More ❯

deployed models, making necessary adjustments. Minimum Qualifications: Minimum of 8 years of relevant work experience and a Bachelor's degree or equivalent experience. Extensive experience with ML frameworks like TensorFlow, PyTorch, or scikit-learn. Expertise in cloud platforms (AWS, Azure, GCP) and tools for data processing and model deployment. Preferred Qualification: MSc or equivalent experience in a quantitative field More ❯

with 6 years, or PhD with 4 years Proficiency in data science languages and tools (e.g., Python, R, SQL, Jupyter, Pandas, Scikit-learn) Experience with machine learning frameworks (e.g., TensorFlow, PyTorch) and big data platforms (e.g., Spark, Hadoop) Strong background in statistics, data modeling, and algorithm development Ability to explain complex data findings to technical and non-technical stakeholders More ❯

Science (or related field). 3+ years of experience writing production-grade Python code. 3+ years of hands-on experience with core Python data libraries (e.g., pandas, numpy, sklearn, tensorflow, pytorch, matplotlib). At least 1 year of experience deploying machine learning models in production environments. 1-2 years of experience working with SQL/NoSQL databases (e.g., Elasticsearch More ❯

developing underwriting or behavioural models for credit extension Desired: Master's degree in Data Science/Machine Learning or related discipline Knowledge of Deep Learning frameworks, ideally Keras/Tensorflow Familiarity with software version control (GitHub, bitbucket) Knowledge of Tableau Ability to comprehend research papers and possibly apply their solutions Credit card industry knowledge What's in it for More ❯

series analysis, anomaly detection, forecasting, or Natural Language Processing (NLP). Strong proficiency in Python/R and expertise with AI/ML libraries/frameworks (e.g., scikit-learn, TensorFlow, PyTorch, Keras). Solid understanding of statistical modelling, econometric techniques, data manipulation, and experience with large datasets/distributed computing; familiarity with Generative AI is a plus. Excellent problem More ❯

into production systems. Collaborate with data scientists, engineers, and product teams to define AI solutions. Ensure scalability, performance, and ethical AI practices. Required Skills & Experience: Strong experience in Python, TensorFlow, PyTorch, Scikit-learn or similar frameworks. Solid understanding of machine learning, deep learning, NLP, or computer vision. Hands-on with data engineering, model deployment (MLOps), and cloud platforms (AWS More ❯