1 to 25 of 376 Permanent PyTorch Jobs

field. 7+ years of professional software development experience, with at least 3 years in AI/ML. Strong proficiency in Python , including libraries like NumPy, Pandas, Scikit-learn, TensorFlow, PyTorch . Solid understanding of ML algorithms , NLP , deep learning , and statistical methods. Experience with Docker, Kubernetes , and cloud platforms like AWS/Azure/GCP . Hands-on experience with More ❯

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 visualization techniques. Familiarity More ❯

and deploying AI/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, Google Cloud, Azure) and containerization technologies (e.g. More ❯

collaboration skills Full right to work in the UK (we are unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits: 💰 Competitive Salary More ❯

collaboration skills Full right to work in the UK (we are unable to offer visa sponsorship for this role) Desirable (Not Essential): Familiarity with deep learning frameworks (e.g. TensorFlow, PyTorch) Exposure to cloud platforms (AWS, GCP, or Azure) Experience with experimental design, research methods, or academic publishing Understanding of MLOps, version control (Git), or containerisation (e.g. Docker) Benefits: 💰 Competitive Salary More ❯

and advanced analytics to generate business value and change, including optimisation of production processes Great knowledge of Python and in particular, the classic Python Data Science stack (NumPy, pandas, PyTorch, scikit-learn, etc) is required; Familiarity with PySpark is also desirable. A cloud platform experience (e.g Azure, AWS, GCP), we're using Azure in the team. Good SQL understanding in More ❯

in production environments Continuously optimise models based on real-world feedback Maintain clear documentation for workflows and models Required Skills: Strong Python skills + ML libraries (scikit-learn, TensorFlow, PyTorch) Solid understanding of data preprocessing & feature engineering Knowledge of supervised, unsupervised, and deep learning methods Experience in model evaluation & tuning Familiarity with AWS, GCP, or Azure is a plus Strong More ❯

lifecycle of ML projects, including initial conceptualization, data handling, model development, and deployment. Proficiency in programming languages, including Python. Experience with machine learning frameworks and libraries such as TensorFlow, PyTorch, Scikit-Learn, etc. Experience developing Python APIs using tools such as FastAPI. Knowledge of database technologies (SQL, MongoDB, Databricks) and data pipeline tools. Familiar with ML CI/CD pipelines More ❯

real-world use cases Contribute to code reviews, testing, and documentation Required Skills & Experience Strong proficiency in Python and its AI/ML ecosystem (e.g. NumPy, Pandas, Scikit-learn, PyTorch, TensorFlow) Experience with machine learning model development , training, and deployment Familiarity with LLMs , NLP , or computer vision techniques Solid understanding of software engineering principles and version control (Git) Experience working More ❯

in machine learning. Optimization : Continuously improve machine learning infrastructure and production workflows. Strong technical foundation in machine learning and software engineering Proficiency in Python and ML libraries (e.g., TensorFlow, PyTorch, scikit-learn) Experience with cloud platforms (AWS, GCP, Azure) Experience with CI/CD pipelines for machine learning (e.g., Vertex AI) Familiarity with data processing tools like Apache Beam/ More ❯

knowledge and familiarity with 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, conversational AI, and natural language processing frameworks. More ❯

plus. Understanding of Machine Learning Fundamentals: A solid understanding of machine learning concepts, including algorithms, data pre-processing, model evaluation, and training. Familiarity with ML frameworks such as TensorFlow, PyTorch, and scikit-learn is beneficial. DevOps Practices: Experience with DevOps practices, including continuous integration and continuous deployment (CI/CD), containerisation using Docker, and Infrastructure as Code (IaC) methodologies. Cloud More ❯

testing, monitoring, and continuous integration Requirements: 3+ years of experience in software engineering, with a focus on AI/ML integration Proficiency in Python and ML frameworks such as PyTorch or TensorFlow Strong grasp of software architecture and microservices Experience working in containerised environments (Docker, Kubernetes) Familiarity with CI/CD pipelines, secure deployment practices and cloud deployment (e.g., AWS More ❯

in AI/ML, LLMs, and GenAI technologies. To Be Successful in The Role, You Will Have Required Skills: Proficiency in Python and machine learning framework s (e.g., TensorFlow, PyTorch, Scikit-Learn). Hands-on experience with OpenAI APIs and Microsoft Azure AI services. Strong understanding of large language models, prompt engineering, and fine-tuning techniques. Experience with data manipulation More ❯

solutions Own critical platform components from conception through production deployment Who You Are Expert proficiency in Python, JavaScript, and modern web frameworks Deep experience with AI/ML frameworks (PyTorch, TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation More ❯

solutions Own critical platform components from conception through production deployment Who You Are Expert proficiency in Python, JavaScript, and modern web frameworks Deep experience with AI/ML frameworks (PyTorch, TensorFlow, Transformers, LangChain) Mastery of prompt engineering and fine-tuning Large Language Models Proficient in vector databases (Pinecone, Weaviate, Milvus) and embedding technologies Expert in building RAG (Retrieval-Augmented Generation More ❯

/ABILITIES Strong programming skills in Python, C++, or similar languages commonly used in AI/ML and CV applications. Proficiency in libraries and frameworks such as OpenCV, TensorFlow, PyTorch, and Scikit-learn. Ability to analyze large image datasets and implement efficient automation for feature extraction and classification. Skilled in deploying software to secure cloud or hybrid environments. Exceptional problem More ❯

Machine Learning, Computer Science, Engineering, Statistics, or equivalent fields • Strong mathematical background (linear algebra, calculus, probability & statistics) • Experience with machine learning model training and analysis through open-source frameworks (Pytorch, Tensorflow, Sklearn) • Experience crafting, conducting, analyzing, and interpreting experiments and investigations. • Experience with modern software development tools and practices (Git, pull requests) • Experience analyzing model performance with relevant metrics and More ❯

familiarity with core ML concepts (classification, time-series, statistical modeling) and their real-world tradeoffs. Fluency in Python and commonly used ML libraries (e.g. pandas, scikit-learn; experience with PyTorch or TensorFlow is a plus). Experience with model lifecycle management (MLOps), including monitoring, retraining, and model versioning. Ability to work across data infrastructure, from SQL to large-scale distributed More ❯

Machine Learning Engineer or similar role. Strong knowledge of machine learning algorithms, statistics, and predictive modeling Proficiency with Python and machine learning toolkits like pandas, scikit-learn, and optionally pytorch/tensorflow. Experience with machine learning operations (MLOps) and productionization of ML models. Familiarity with building data and metric generation pipelines, using tools like SQL or Spark, to answer business More ❯

Exposure to tools like KServe, Ray Serve, Triton, or vLLM is a big plus Bonus Points Experience with observability frameworks like Prometheus or OpenTelemetry Knowledge of ML libraries: TensorFlow, PyTorch, HuggingFace Exposure to Azure or GCP Passion for financial services Qualifications Degree in Computer Science, Engineering, Data Science, or similar What We Offer A collaborative and innovative work environment with More ❯

systems, edge computing and cloud systems (AWS, Azure), e.g., microservices, event-streaming/messaging, container orchestration (Docker, Kubernetes), DevOps Experience building applications using deep learning frameworks like Keras, Tensorflow, PyTorch in either production or research settings Has experience with the machine learning product lifecycle as well as runtime integration and performance optimization Knowledge in Siemens Software solutions (e.g. Industrial Edge More ❯

and deliver on project objectives. Masters degree in a STEM field (maths, science, engineering etc.) or equivalent Strong programming skills in Python (e.g., NumPy, Pandas, scikit-learn, TensorFlow/PyTorch). Demonstrable experience in creating and developing Python libraries. Demonstrable experience designing, implementing and training machine learning models from scratch. Strong foundations in applied mathematics and physics, particularly in statistical More ❯

stakeholders. Familiarity with the Model Risk Management (MRM) lifecycle, including model documentation, testing, validation, and alignment with governance and compliance frameworks. Proficiency in Pythonand tools such as LangChain, Pandas, PyTorch/TensorFlow, and FastAPI. Strong understanding of prompt engineering, RAG pipelines, vector databases (e.g., FAISS, Chroma), and LLM evaluation strategies. Familiarity with software engineering best practices, including: REST API design More ❯

year hands-on experience in AI or ML in a professional environment (3-5 years preferred) Strong knowledge of machine learning model development, deployment, and modern ML libraries (TensorFlow, PyTorch, scikit-learn, etc.) Solid programming background with experience using statistical and signal analysis libraries Experience with neural network architectures including deep learning models Understanding of transformer architectures and attention mechanisms More ❯