151 to 175 of 425 Permanent PyTorch Jobs

CD pipelines (GitLab), and containerization (Docker). Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions. Product mindset: Ability to think from the user's perspective and design solutions that align with More ❯

CD pipelines (GitLab), and containerization (Docker). Strong Python programming skills: Strong programming skills in Python, including its ecosystem for AI/ML, with experience using libraries such as PyTorch, Hugging Face Transformers, scikit-learn, and TensorFlow to build and implement AI-driven solutions. Product mindset: Ability to think from the user's perspective and design solutions that align with More ❯

current with emerging techniques. You are experienced in multivariate testing, mentoring junior scientists, and leading technical decisions. You are proficient in Python, Java, Scala, and ML frameworks (e.g., TensorFlow, PyTorch ), with experience in cloud platforms (AWS), big data (Spark), and deployment tools (Kubernetes, Airflow, Docker). Accommodation requests If you need assistance with any part of the application or recruiting More ❯

Working with Data Scientists to deploy trained machine learning models into production environments Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch Experience with software engineering best practices and developing applications in Python. Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one of the 3 major cloud More ❯

Working with Data Scientists to deploy trained machine learning models into production environments Working with a range of models developed using common frameworks such as Scikit-learn, TensorFlow, or PyTorch Experience with software engineering best practices and developing applications in Python. Technical experience of cloud architecture, security, deployment, and open-source tools ideally with one of the 3 major cloud More ❯

how of designing and implemention synchronous, asynchronous and batch data processing operations Expert level programming skills in Python, along with experience in using relevant tools and frameworks such as PyTorch, FastAPI and Huggingface; strong programming skills in Java are a plus Expert level know-how of ML Ops systems, data pipeline design and implementation, and working with ML platforms (preferably More ❯

this is essential as you'll be the domain expert from day one. Excellent Python programming skills and strong familiarity with ML libraries such as scikit-learn, XGBoost, TensorFlow, PyTorch, Keras etc. Proven track record deploying ML models to production (API, batch, or streaming contexts) Solid understanding of the modern software engineering, infrastructure and data technologies Experience working with LLMs More ❯

Including you. What you'll need Proven experience in leading data science projects in cybersecurity, fraud, or behavioural analytics. Data Engineering - Deep expertise in Python, ML frameworks (e.g. TensorFlow, PyTorch), and cloud platforms (preferably GCP). Deep Learning Theory & Applications - Strong grasp of anomaly detection, time-series modelling, and deep learning architectures. Experience with LLMs and generative AI in production More ❯

Engineering, or related technical field 2+ years of experience in AI/ML development with a focus on practical applications Strong proficiency in Python and relevant AI libraries (TensorFlow, PyTorch, Hugging Face) Hands-on experience with workflow automation platforms like N8N, AirTable, and proven track-record. Experience with AI agent development and testing methodologies using Google ADK, LangGraph, Llamaindex Understanding More ❯

Scientific publications in top-tier AI and neuroscience conferences (NeurIPS, ICLR, ICML, AAAI, CVPR, Cosyne, SFN, CNN ecc) or peer reviewed journals Familiarity with deep learning libraries such as Pytorch, Huggingface, Transformers, Accelerator and Diffuser. Hands-on experience in training and fine-tuning generative models like diffusion models or large language models such as GPTs and LLAMAs. Experience with data More ❯

Scientific publications in top-tier AI and neuroscience conferences (NeurIPS, ICLR, ICML, AAAI, CVPR, Cosyne, SFN, CNN ecc) or peer reviewed journals Familiarity with deep learning libraries such as Pytorch, Huggingface, Transformers, Accelerator and Diffuser. Hands-on experience in training and fine-tuning generative models like diffusion models or large language models such as GPTs and LLAMAs. Experience with data More ❯

Design of Experiment (DoE) Solid understanding of unit operations and process-structure-property-performance relationships in foods. Hands-on experience with machine learning, preferably in Python (scikit-learn, TensorFlow, PyTorch, etc.). Experience with hybrid modelling approaches (combining mechanistic and data-driven models) is a plus. Familiarity with digital twin technologies and in silico experimentation concepts. Collaborative mindset and ability More ❯

of delivering and scaling models that solve complex, real-world problems Deep understanding of machine learning concepts and experience applying them in production settings, using frameworks such as Transformers, PyTorch, or TensorFlow Strong Python skills, with the ability to write clean, modular, production-grade code, and a solid understanding of data engineering and MLOps principles Ability to lead end-to More ❯

of delivering and scaling models that solve complex, real-world problems Deep understanding of machine learning concepts and experience applying them in production settings, using frameworks such as Transformers, PyTorch, or TensorFlow Strong Python skills, with the ability to write clean, modular, production-grade code, and a solid understanding of data engineering and MLOps principles Ability to lead end-to More ❯

a strong grasp of DevSecOps best practices in cloud-native environments • Hands-on experience with key tools and frameworks, including: o Python, NumPy, Pandas, scikit-learn o TensorFlow or PyTorch o Elasticsearch, Logstash, Kibana • Preferred Experience in GDS (Government Digital Services) or USDS (U.S. Digital Services) Education Requirement • Shall have at a minimum, a bachelor's degree in computer science More ❯

developing proof of concepts of new technologies and evaluating the state of the art in machine learning algorithms for text analytics Demonstrated experience with machine learning frameworks such as PyTorch, Keras, Tensorflow Demonstrated experience with data visualization tools (i.e. Tableau, Pandas, D3.js, ggplot, etc) Demonstrated experience with NoSQL data stores such as MongoDB or DynamoDB Demonstrated experience using Natural Language More ❯

innovative improvements. Qualifications: Proven experience as an MLOps engineer or similar role with a focus on 3D applications Strong programming skills in Python, and familiarity with ML frameworks (TensorFlow, PyTorch, etc.) Expertise in 3D reconstruction and rendering Experience with cloud platforms (AWS, GCP, Azure) and container orchestration (Kubernetes, Docker) Excellent problem-solving skills and ability to work cross-functionally in More ❯

if, and surprise us again, and again. Proven track record delivering impactful ML/AI solutions in production. Deep expertise in Python and modern AI/ML frameworks (e.g., PyTorch, TensorFlow, scikit-learn, NumPy, Pandas). Hands-on experience with GenAI, agentic AI, and automated testing for AI systems. Curiosity and creativity to challenge assumptions and explore new approaches. Strong More ❯

reinforcement learning and imitation learning Contribute to creating multi-robot systems and cross-embodiment learning techniques Drive innovation by publishing research and attending top conferences Engineer Background: Expertise in PyTorch or TensorFlow, distributed computing, and multi-GPU training Robotics experience, particularly in reinforcement/imitation learning Experience in cloud infrastructure (AWS, GCP, or Azure) and containerization Ability to translate research More ❯

reinforcement learning and imitation learning Contribute to creating multi-robot systems and cross-embodiment learning techniques Drive innovation by publishing research and attending top conferences Engineer Background: Expertise in PyTorch or TensorFlow, distributed computing, and multi-GPU training Robotics experience, particularly in reinforcement/imitation learning Experience in cloud infrastructure (AWS, GCP, or Azure) and containerization Ability to translate research More ❯

DeepCell Integrating ML workflows with platforms such as Benchling , PubMed APIs , and internal R&D systems Supporting model validation, performance benchmarking, and regulatory documentation Key Technologies & Tools: ML Frameworks: PyTorch, TensorFlow, Hugging Face Transformers Bio-AI Tools: AlphaFold, RoseTTAFold, BioBERT, DeepCell, Cellpose Data Sources: Genomic datasets, microscopy images, biomedical literature Cloud & DevOps: AWS/GCP, Docker, Kubernetes, MLflow Languages: Python More ❯

loss functions, and deploying production-ready solutions) Familiarity in statistical methods for Machine Learning (e.g. Bayesian methods, HMMs, graphical models, dimension reduction, clustering, classification, regression techniques, etc.) Familiarity with PyTorch, TensorFlow, JAX or similar frameworks Strong coding abilities in Python Preferred Qualifications Experience in the Architecture, Engineering, and/or Construction domains, including expertise with industry-specific data formats (e.g. More ❯

on trends in ML models, software stacks, and hardware architectures. PREFERRED EXPERIENCE: Proficiency in Python and C/C++ programming. Deep understanding of AI/ML algorithms, frameworks (e.g., PyTorch, ONNX), and model representations. Experience in analytical modeling of ML operators regarding compute and data movement. Background in optimization libraries and solvers like PuLP, CBC, Gurobi is advantageous. Effective communication More ❯

re Looking For: 0–2 years of experience in machine learning, applied AI, or data science (personal projects and internships count!) Solid Python skills and familiarity with libraries like PyTorch, TensorFlow, or Hugging Face Transformers Understanding of basic ML concepts and data preprocessing techniques Interest in NLP, unstructured data, and information extraction Eagerness to learn, take feedback, and contribute to More ❯

re Looking For: 0–2 years of experience in machine learning, applied AI, or data science (personal projects and internships count!) Solid Python skills and familiarity with libraries like PyTorch, TensorFlow, or Hugging Face Transformers Understanding of basic ML concepts and data preprocessing techniques Interest in NLP, unstructured data, and information extraction Eagerness to learn, take feedback, and contribute to More ❯