276 to 300 of 2,219 PyTorch Jobs

Platform (GCP) AI/ML services, especially Vertex AI (Workbench, Training, Prediction, Pipelines, Feature Store). • Proficiency in Python and strong experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, JAX, Hugging Face Transformers). • Experience with data engineering and building robust data pipelines for AI/ML workloads on GCP (e.g., BigQuery, Dataflow). • Solid understanding of core AI More ❯

model performance in production Contribute to our AI platform infrastructure and help scale our solutions What They Are Looking For Proven experience in computer vision and deep learning (e.g., PyTorch, TensorFlow, OpenCV) Strong software engineering skills in Python and/or C++ Solid understanding of neural networks, image processing, and machine learning fundamentals Familiarity with cloud platforms (AWS, GCP, or More ❯

Position Requirements Experience: 3-5 years of hands-on experience in AI and machine learning. Technical Expertise: Strong proficiency in Python. Expertise in machine learning frameworks such as TensorFlow, PyTorch, Keras, or similar. Machine Learning: Solid understanding of supervised and unsupervised learning, deep learning (CNNs, RNNs, GANs), and reinforcement learning. Data Handling: Proficient in data manipulation and analysis using tools More ❯

areas of machine learning at major conferences (NeurIPS, ICML, EMNLP, CVPR, etc.) and/or journals Strong high-level programming skills (e.g., Python), frameworks and tools such as DeepSpeed, Pytorch lightning, kubeflow, TensorFlow, etc. Strong written and verbal communication skills to operate in a cross functional team environment More ❯

Experience with retrieval-augmented generation (RAG) systems Knowledge of optimization techniques for reducing LLM latency and computational costs Software Engineering & Architecture Strong Python development skills (pandas, numpy, scikit-learn, PyTorch/TensorFlow) Experience with web frameworks (Streamlit, FastAPI, or Flask) and frontend technologies Database design and optimization (PostgreSQL preferred) for large protein datasets API development and integration, especially for interfacing More ❯

Scientist 's working across a variety of companies & industries Provide hands-on coding sessions and real-world project mentorship using Python and relevant ML libraries (e.g., Scikit-learn, TensorFlow, PyTorch etc) Incorporate cloud-based tools and services (e.g., AWS, GCP, or Azure) into training to simulate modern ML engineering environments (Cloud Training can be provided to you) Keep training material More ❯

Operations Research, Optimization, Data Science) with relevant industry or research experience, or an MS with equivalent experience. Practical experience with machine learning and deep learning toolkits such as TensorFlow, PyTorch, NumPy, Scikit-Learn, Pandas. Ability to design experiments, training frameworks, and evaluate model performance aligned with business goals. Experience with big data, scalable model training, and effective communication of technical More ❯

experience in AI/ML development. Strong understanding of AI/ML algorithms and techniques, including LLMs, GenAI, and automated AI systems. Experience with machine learning frameworks (e.g., TensorFlow, PyTorch). Must Have: Proficiency in Python, R, or other relevant programming languages. Proficiency in working with large datasets, data wrangling, and data preprocessing. Ability to work independently and lead projects More ❯

You have strong foundational software engineering knowledge, 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 quality, testing, observability More ❯

of-the-art NLP and ML techniques Mastery of several ML frameworks and libraries, with the ability to architect complex ML systems from scratch Extensive experience with Python and PyTorch Track record of contributing to the successful delivery of robust, scalable and production-ready ML models, with a focus on optimising performance and efficiency Experience with the full ML development More ❯

with 4+ years of relevant industry experience. Strong expertise in deep learning, neural networks, and generative models (GANs, diffusion models). Practical experience with modern machine learning frameworks (e.g., PyTorch, TensorFlow). Advanced programming skills in Python . Strong problem-solving, analytical, and communication skills. Demonstrated ability to work effectively in multidisciplinary, fast-paced, research-driven teams. Preferred Qualifications Experience More ❯

or intelligent data extraction pipelines. Deep understanding of NLP fundamentals: text preprocessing, language modelling, and semantic similarity. Strong proficiency in Python, including use of ML libraries such as TensorFlow, PyTorch, or similar. Experience with data science tools and platforms (e.g., Jupyter, Pandas, NumPy, MLFlow). Familiarity with cloud-based AI tools and infrastructure, especially within the AWS ecosystem (SageMaker, Lambda More ❯

looking for a Senior Data Scientist with proven experience leading AI projects and mentoring junior team members. You should have strong expertise in Python, including libraries such as TensorFlow, PyTorch, and Hugging Face Transformers, with a solid understanding of LLM architectures. You should be well-versed in various machine learning techniques, including supervised, unsupervised, and semi-supervised learning, as well More ❯

learning models for tasks like recommendations, segmentation, forecasting, and optimising marketing spend. Proficiency in Python, SQL, Bash, and Git, with hands-on experience in tools like Jupyter notebooks, Pandas, PyTorch, and more. Experience with A/B testing and other experimentation methods to validate model performance and business impact. Experience with cloud platforms (AWS, Databricks, Snowflake), containerisation tools (Docker, Kubernetes More ❯

Exposure to Dash Plotly (or similar Python frameworks like Streamlit) for dashboard creation. Experience with Machine Learning model development and data science workflows (including frameworks such as scikit-learn, PyTorch, or TensorFlow). Experience in Quantitative Finance or strong interest in mathematical/financial modeling, derivatives pricing, or algorithmic trading. Familiarity with ETRM platforms (e.g., OpenLink Endur). Master’s More ❯

written reports and presentations. This role is 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). Git for version control. Cloud experience (we use Azure/GCP/ More ❯

written reports and presentations. This role is 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). Git for version control. Cloud experience (we use Azure/GCP/ More ❯

written reports and presentations. This role is 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). Git for version control. Cloud experience (we use Azure/GCP/ More ❯

written reports and presentations. This role is 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). Git for version control. Cloud experience (we use Azure/GCP/ More ❯

progress, sharing ideas, and collaborating. Engaging with partners to meet their requests. Additional skills we value: Azure Machine Learning Services, Cognitive Services, Responsible AI Dashboard Python, SKLearn, XGBoost TensorFlow, PyTorch Model deployment options like Azure Functions, FastAPI, Kubernetes CI/CD pipelines, Git actions Infrastructure as code: Terraform, ARM Templates, Databricks Asset Bundles Advanced ML techniques: Graph processing, Computer Vision More ❯

in retail-focused data science projects-preferably including segmentation, recommendation engines, inventory optimization, or computer vision applications. Strong hands-on experience with: Python (Pandas, NumPy, Scikit-learn, TensorFlow/PyTorch, XGBoost, etc.) ML Ops practices and frameworks SQL and cloud-based data platforms (e.g., GCP, AWS, Azure) Experience with deploying models in production environments. Familiarity with CV techniques like object More ❯

techniques to create solutions to challenging business problems. We prioritise clean, well-tested code with a culture of documentation and knowledge sharing. Our tech stack includes GCP, Python, GitHub, PyTorch, TensorFlow, Scikit-learn, and XGBoost. With mature infrastructure and dedicated teams for Data Engineering, Analytics, and Platform Engineering, our Data Scientists enjoy high autonomy. We tackle interesting datasets, set up More ❯

on Linux, Go, or similar. Utilise Advanced Technical Stack: Leverage our technical stack, including Python, SQL, PostgreSQL, BigQuery, and libraries such as Pandas, NumPy, SciKit-Learn, XGBoost, Matplotlib, and Pytorch, to develop robust and scalable AI/ML solutions. Strong foundation in data structures, algorithms, and problem-solving, with a clear focus on efficiency and optimisation. Experience with architecting and More ❯

technical or data products through multiple release cycles Strong understanding of data science, machine learning concepts, and analytics capabilities Experience with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, etc.) Experience with MLOps practices (e.g., model deployment, monitoring, retraining workflows) for operationalizing machine learning models effectively Excellent communication skills with the ability to translate complex technical concepts More ❯

technical or data products through multiple release cycles Strong understanding of data science, machine learning concepts, and analytics capabilities Experience with AI/ML frameworks and tools (e.g., TensorFlow, PyTorch, scikit-learn, etc.) Experience with MLOps practices (e.g., model deployment, monitoring, retraining workflows) for operationalizing machine learning models effectively Excellent communication skills with the ability to translate complex technical concepts More ❯