51 to 75 of 631 PyTorch Jobs in England

C#, JavaScript, Kotlin, Java or Go)Experience with Gen AI tools (such as LangGraph, CrewAI, Hugging Face or OpenAI APIs) and ML frameworks like PyTorch or TensorFlowStrong understanding of ML fundamentals (training, evaluation, deployment) and LLM-specific challenges such as prompt engineering, latency and cost optimisationExperience with cloud platforms ...

experience training, deploying, and maintaining machine learning models in production environments Proficiency in Python and relevant AI/ML libraries (e.g. scikit‐learn, TensorFlow, PyTorch) Experience with MLOps practices and tools for managing the machine learning lifecycle Experience building and deploying Generative AI applications, including familiarity with LLMOps Exposure ...

Broad knowledge of MLOps tooling – for versioning, reproducibility, observability etc. Experience monitoring, maintaining, enhancing existing models over an extended time period Extensive experience with pytorch and related data science python libraries (e.g. pandas) Experience of containerising applications or models for deployment (Docker) Experience with one of the major public cloud ...

into production environments. Essential experience includes: Strong commercial development experience with Python , including asynchronous programming. Strong knowledge of the Python machine learning ecosystem, particularly PyTorch, Scikit-learn and NumPy . Experience deploying speech technologies , ideally including both ASR and TTS models. Experience deploying, serving or optimising Large Language Models ...

with a track record of building and maintaining production‐quality systems. Expert‐level Python experience with numerical, statistical, or ML libraries (e.g. NumPy, pandas, PyTorch, JAX, TensorFlow). Deep understanding of statistical modelling, optimisation, or machine‐learning techniques. Experience building and operating backend systems and data pipelines in a cloud ...

Broad knowledge of MLOps tooling – for versioning, reproducibility, observability etc. Experience monitoring, maintaining, enhancing existing models over an extended time period Extensive experience with PyTorch and related data science Python libraries (e.g. pandas) Experience of containerising applications or models for deployment (Docker) Experience with one of the major public cloud ...

Platform, or Microsoft Azure) Knowledge of containerisation technologies like Docker and orchestration tools such as Kubernetes Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, or Java-based ML libraries) Strong problem-solving and communication skillsPreferred Qualifications Experience with NLP, computer vision, or recommendation systems Familiarity with MLOps practices ...

generate actionable insights that inform business and product decisions Desirable: Hands-on coding and prototyping experience in AI/ML development (Python, TensorFlow, PyTorch) Experience with proof-of-concept development and technical validation of new AI technologies Background in data science or machine learning engineering with an understanding of model ...

Platform, or Microsoft Azure) Knowledge of containerisation technologies like Docker and orchestration tools such as Kubernetes Experience with AI/ML frameworks (e.g., TensorFlow, PyTorch, or Java-based ML libraries) Strong problem-solving and communication skills Preferred Qualifications Experience with NLP, computer vision, or recommendation systems Familiarity with MLOps practices ...

NLPBroad knowledge of MLOps tooling – for versioning, reproducibility, observability etc. Experience monitoring, maintaining, enhancing existing models over an extended time periodExtensive experience with pytorch and related data science python libraries (e.g. pandas)Experience of containerising applications or models for deployment (Docker)Experience with one of the major public cloud providers ...

least one major programming language for AI development (e.g., Python, C++)Familiarity with relevant AI/ML frameworks and libraries such as TensorFlow, PyTorch, scikit-learn, or KerasUnderstanding of data structures, algorithms, and good software engineering practicesSome hands-on experience with AI/ML projects through academic coursework, research, internships ...

technologies. Strong programming skills in Python and experience with SQL and large-scale data processing technologies. Experience with modern machine learning frameworks such as PyTorch, TensorFlow, scikit-learn, or equivalent technologies. Strong understanding of statistical analysis, experimentation, hypothesis testing, model evaluation, and performance measurement. Experience working with large volumes ...

shipping models to production and supporting them post-deployment.* Strong Python programming skills, including object-oriented design and proficiency with key ML libraries (e.g., PyTorch, TensorFlow, Scikit-Learn).* Solid understanding of probability and statistical modeling to support robust model development and interpretation.* Experience with cloud platforms (especially Azure ...

Experience Strong experience building and deploying machine learning solutions in production environments. Advanced Python skills and experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. Experience working with cloud technologies such as AWS, Azure, or GCP. Strong understanding of MLOps, CI/CD, and machine learning lifecycle ...

Strong experience developing and deploying machine learning models in production environments. Excellent Python development skills and experience with machine learning frameworks such as TensorFlow, PyTorch, or Scikit-learn. Experience working with cloud platforms such as AWS, Azure, or GCP. Strong understanding of MLOps, CI/CD principles, and model lifecycle ...

biomedical data; Knowledge of Azure, AWS, or GCP and model deployment using MLOps frameworks; Strong Python and SQL programming skills, with experience in PyTorch, TensorFlow, and Hugging Face; Experience with Databricks, Spark, and other data platforms and big data frameworks; Excellent communication skills for engaging C-level stakeholders and aligning ...

training, deploying, and maintaining machine learning models in production environments Proficiency in Python and relevant AI/ML libraries (such as scikit-learn, TensorFlow, PyTorch) Experience with MLOps practices and tools for managing the machine learning lifecycle Experience building and deploying Generative AI applications, including familiarity with LLMOps Exposure ...

optimisation problems. Proficient in SQL & Python. Familiarity with data manipulation libraries (e.g. PySpark, Pandas, Numpy) and machine learning frameworks (e.g. scikit-learn, TensorFlow or PyTorch). Experience with MLOps tools (e.g., MLflow, Databricks Model Registry, Unity Catalog, Vertex AI) and version control (Git). Strong coding practices with experience ...

technologies (Azure, AWS or GCP) and model deployment using MLOps frameworks Strong programming skills in Python and SQL with experience in frameworks such as PyTorch, TensorFlow and Hugging Face Experience using data platforms and big data frameworks like Databricks and Spark Excellent communication skills for engaging C-level stakeholders ...

including orchestration frameworks, context and memory management, and interoperability protocols such as MCP Experience with machine learning frameworks and data science packages such as PyTorch, TensorFlow, scikit‐learn, NumPy, pandas, SciPy, and statsmodels Experience deploying to AWS, including services such as SageMaker and Bedrock, and operating production large language model ...

model packaging and release management, automated validation, monitoring, and lifecycle management Working knowledge of ML/DL frameworks and tooling (e.g. PyTorch/TensorFlow and the Python ML ecosystem) sufficient to collaborate effectively with data scientists and implement inference pipelines Experience working with complex, multi-layered datasets (including imbalanced data ...

model packaging and release management, automated validation, monitoring, and lifecycle management Working knowledge of ML/DL frameworks and tooling (e.g. PyTorch/TensorFlow and the Python ML ecosystem) sufficient to collaborate effectively with data scientists and implement inference pipelines Experience working with complex, multi-layered datasets (including imbalanced data ...

experience training, deploying, and maintaining machine learning models in production environmentsProficiency in Python and relevant AI/ML libraries (such as scikit-learn, TensorFlow, PyTorch)Experience with MLOps practices and tools for managing the machine learning lifecycleExperience building and deploying Generative AI applications, including familiarity with LLMOpsExposure to cloud platforms ...

security, and compliance. Lead technical reviews and provide guidance on complex AI engineering challenges. Technical Expertise: Deep expertise in AI/ML frameworks—TensorFlow, PyTorch, Scikit‐Learn, Transformers—cloud platforms (AWS, Azure, GCP), and modern software engineering practices. Strong background in deep learning, natural language processing, computer vision, or reinforcement ...

designing and implementing machine learning solutions, including model training, deployment, and inference at scale, with working knowledge of AI/ML frameworks such as PyTorch, TensorFlow, Hugging Face, and scikit-learn. You have a background in a customer-facing technical role (solutions architect, ML engineer, data scientist, or technical consultant ...