1 to 25 of 73 Permanent PyTorch Jobs in the City of London

algorithms, statistical methods, and predictive modeling Experience with NLP techniques for text analysis, classification, and information extraction Knowledge of deep learning frameworks such as PyTorch or TensorFlow Experience with data visualization tools (Matplotlib, Seaborn, Plotly, or similar) Knowledge of MLOps practices and tools for experiment tracking Strong analytical mindset with ...

data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data pipelines for analytics ...

engineering, security, and product teams to deliver at pace and scale. The toolkit you’ll use 🌳 Data Science & Engineering: Python (NumPy, Pandas, scikit-learn, PyTorch/TensorFlow), SQL, NoSQL, Spark, big data ecosystems Visualisation & APIs: REST/JSON, Postman, Flask/FastAPI, Power BI/Tableau, D3.js DevOps & Cloud ...

related discipline Demonstrated project experience (academic research, dissertation work, or personal projects) applying machine learning or AI techniques Strong programming skills in Python (e.g. PyTorch, TensorFlow, scikit-learn, pandas, NumPy) Familiarity with cloud platforms (AWS, Azure, or GCP) and basic distributed systems concepts Strong problem-solving mindset with a passion ...

Hands-on expertise with Generative AI (LLMs, prompt engineering, fine-tuning). Proficiency in Python and familiarity with deep learning/NLP libraries (LangChain, PyTorch, TensorFlow, HuggingFace Transformers). Experience with building Q&A systems and retrieval-augmented generation pipelines. Knowledge of vector databases or semantic search concepts. Familiarity with ...

5+ years of technical leadership experience managing a team of Data Scientists and ML Engineers. Expertise: Expert-level proficiency in core ML frameworks (e.g., PyTorch, TensorFlow) and data science languages (Python). Generative AI: Proven experience building a commercial practice or product focused on Generative AI and Large Language Models ...

deep understanding of machine learning algorithms, deep learning, and generative models. Advanced AI Skills and Testing: Familiarity with deep learning frameworks (e.g., TensorFlow, PyTorch), hands-on experience in deploying AI/ML solutions as a service/REST API on Cloud or Kubernetes, and proficiency in testing of developed ...

demos and workshops. Experience leading team of AI/software engineers Experience driving productivity and cost optimisations Skills: Python with AI/ML frameworks (PyTorch, TensorFlow). Prompt Engineering, Langchain, Langsmith/Langfuse, Gen AI/Agentic AI, Cloud platforms (Azure AI Foundry, AWS Sagemaker/Bedrock, GCP Vertex ...

portfolio of relevant projects. Track record of delivering end-to-end ML solutions integrated into SaaS products Proficiency in Python with libraries like TensorFlow, PyTorch, or Scikit-learn for ML, and Pandas, PySpark, or similar for data processing. Experience designing and orchestrating data pipelines with tools like Apache Airflow, Spark ...

Academic Excellence: BSc or MSc in Computer Science, AI, Data Science, or related technical field from a top university Familiarity with frameworks such as PyTorch, Hugging Face, LangChain, or LlamaIndex Passionate about sports, health, or fitness – you’ll feel right at home here Bonus points if you: Have worked with ...

such as NLP, images, audio, graphs, time series and tabular data Advanced Python skills with experience using libraries such as pandas, numpy, scikit-learn, PyTorch, transformers, statsmodels or PyMC Strong understanding of software and ML engineering best practice (e.g. version control, packaging, model deployment) Ability to communicate complex technical concepts ...

data pipelines and ML models using modern libraries across multiple domains: Data science stack: NumPy, pandas/polars, scikit-learn, XGBoost, LightGBM Deep learning: PyTorch, JAX Statistical programming: NumPyro, PyMC Data skills: Proficient in SQL, with the ability to write efficient, maintainable queries and manage data pipelines for analytics ...

services. Strong foundation in software engineering principles for building scalable, maintainable, and production-ready AI systems. Proficiency in Python with AI/ML frameworks (PyTorch, TensorFlow). Experience with MLOps/LLMOps tools (MLflow, Kubeflow, Docker, Kubernetes). Deep proficiency in Python and extensive experience with relevant AI/ ...

inclusive team environment that encourages continuous learning and improvement. Your Profile Essential skills/knowledge/experience: Knowledge of machine learning frameworks (e.g., PySpark, PyTorch ) and model deployment tools (e.g., MLflow, TensorFlow Serving). Strong experience with data processing frameworks (e.g., Apache Spark, Flink). Expertise in SQL and NoSQL ...

Python with experience building backend systems Background in developing infrastructure to support machine learning projects Practical experience deploying models using frameworks such as PyTorch, TensorFlow, or scikit-learn Familiarity with tools like Docker and Kubernetes for containerised deployments Experience working with cloud platforms such as AWS, Azure, or GCP, including ...

experience as a data scientist in industry or related environments. Proficiency in Python and common ML/data libraries (e.g., pandas, numpy, scikit-learn, PyTorch, transformers). Understanding of software and ML engineering best practices (git, package development, model deployment). Experience with cloud platforms, particularly AWS, for training ...

share learnings across the team. Requirements: Hands-on experience developing and deploying ML models in Python using frameworks such as scikit-learn, XGBoost, PyTorch, or TensorFlow. Strong experience with AWS ML services (SageMaker, Lambda, S3) in production environments. Strong experiment design skills: hypothesis formulation, A/B testing, and statistical ...

scientist in industry or similar environment. • Good knowledge of python, along with common machine learning and data analysis libraries (e.g. pandas, numpy, scikit-learn, pytorch, transformers, statsmodels, pymc). • Ability to absorb complex new scientific concepts and quickly get up to speed on new areas of the literature. • Good understanding ...

marketing optimisation, conversational AI, or related domains. Expert Python and SQL. Strong system design and engineering fundamentals. Hands-on with ML frameworks: sklearn, XGBoost, PyTorch, TensorFlow, LightGBM. Experience with LLMs, prompt design, RAG, evaluation frameworks. Familiarity with data engineering and modern MLOps (registries, pipelines, CI/CD, monitoring). Cloud ...

model serving, versioning, and lifecycle management Lead documentation, knowledge transfer, and mentoring to upskill internal teams Technical requirements Strong Python and ML frameworks (PyTorch, TensorFlow) MLOps tooling (MLflow, Kubeflow or similar) Docker, Kubernetes, CI/CD pipelines Cloud platforms (AWS, Azure or GCP); Terraform experience preferred Financial services experience highly ...

Profile Experience: From 1 year in data science or analytics to Principal-level leadership Proficiency in Python, R, SQL , and familiarity with Spark, TensorFlow, PyTorch Strong knowledge of machine learning, statistical modeling, and data engineering principles Experience with cloud platforms (AWS, Azure, GCP) Excellent communication and client-facing skills Active ...

with machine learning, NLP, or information retrieval projects, preferably with language models. Proficiency in Python and familiarity with deep learning/NLP libraries (Langchain, PyTorch, TensorFlow, HuggingFace Transformers). Knowledge of vector databases or semantic search concepts is desirable. Eagerness to learn, strong problem-solving skills, and ability to work ...

applied AI roles. Recent, demonstrable experience with LLMs, Generative AI, and/or RAG-based systems . Strong Python skills using frameworks such as PyTorch, TensorFlow, Hugging Face, or Google GenAI . Experience with vector databases and retrieval-based architectures. Proven experience designing and operating large-scale ML systems ...

Experience building robust systems for ML applications Proven track record deploying machine learning models in production (using frameworks such as Scikit-learn, TensorFlow, or PyTorch) Practical experience working with cloud infrastructure (e.g., AWS, Azure, GCP) and a good understanding of architecture, security, and scaling Hands-on experience with Docker ...

achieve reliable results. True ML Fundamentals: You aren't limited to APIs. You have a background in training and evaluating models (TensorFlow/PyTorch/Keras/Scikit-learn) and know when a simple classifier is better than a generative model. Data Fluency: You understand how to build datasets from ...