1 to 25 of 58 Permanent PyTorch Jobs in the City of London

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 ...

Required Skills & Qualifications Education: Bachelor’s or Master’s in Computer Science, Data Science, Mathematics, or related field. Programming: Strong proficiency in Python (TensorFlow, PyTorch, Scikit-learn), and experience with SQL. ML Expertise: Solid understanding of supervised/unsupervised learning, deep learning, and model evaluation techniques. Cloud & MLOps: Experience with ...

roles, with proven success in delivering end-to-end projects. Strong proficiency in Python , R , and data science libraries (Pandas, NumPy, Scikit-learn, TensorFlow, PyTorch). Expertise in multi-cloud environments (AWS, Azure, GCP) including services like S3, BigQuery, Azure ML, etc. Solid understanding of data engineering principles ...

Experience & Skills * 2-4 years in production-level AI/ML delivery. * Legal/professional services experience is a plus. * AI/ML frameworks: PyTorch, TensorFlow, LangChain. * Cloud: Azure (preferred), AWS, GCP. * MLOps: CI/CD, model lifecycle, monitoring. * Generative AI: LLMs, RAG, chat agents. * Data engineering alignment: ETL, governance. ...

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 ...

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 ...

processing, Bayesian statistics, time-series forecasting, collaborative filtering etc) ● Proficiency in Python with familiarity to ML libraries e.g. pandas, numpy, scipy, scikit-learn, tensorflow, pytorch) ● Familiarity with cloud platforms (GCP, AWS, Azure) and tools like Dataiku, Databricks. ● Experience with ML Ops, including model deployment, monitoring, and retraining pipelines. ● Ability ...

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 ...

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 ...

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 ...

with data visualization tools like Power BI. Familiarity with data manipulation libraries such as Pandas and NumPy. Knowledge of machine learning frameworks like TensorFlow, PyTorch, or Scikit-learn. Excellent problem-solving skills and attention to detail. Ability to work effectively both independently and as part of a team. Strong communication ...

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 ...

boosting, random forests, and ensemble methods Experience with generative models (GANs, VAEs, Diffusion models) Programming & Tools : Expert-level Python programming Proficiency with ML frameworks (PyTorch, TensorFlow, JAX) Experience with scikit-learn, XGBoost, LightGBM Strong software engineering practices and clean code principles Data & Computing : Experience with big data technologies (Spark, Dask ...

with production optimisation for RAG systems, including latency, token cost control, context window constraints, monitoring and prompt versioning Strong Python skills and experience with PyTorch, TensorFlow or Keras Exposure to MLOps practices and hands-on experience with Sagemaker and/or Vertex AI Bachelor's degree in a technical field ...

Learning Modelling : Experience with a variety of ML techniques ( regression, classification, clustering, time-series forecasting ) Experience with deep learning frameworks such as Keras or PyTorch Model Deployment : Proven ability to productionise models, including building and deploying APIs Strong visualization and communication skills , with the ability to translate complex technical findings ...

desirable experience Experience with large-scale ML systems (model training, serving, platforms) Experience supporting or working inside ML research teams Familiarity with ML frameworks (PyTorch, TensorFlow etc) Experience building pipelines for scientific or healthcare data Knowledge of cluster compute, distributed training and GPUs Understanding of healthcare data or regulated environments ...

Technical Expertise: •Proven experience in data science leadership roles with team management. •Strong expertise in Azure Machine Learning, Python, and ML frameworks (TensorFlow, PyTorch, Scikit-learn). •Hands-on experience with MLOps, CI/CD pipelines, and model monitoring. •Knowledge of cloud architecture, data engineering, and security best practices. •Design ...

Kubeflow, etc.) and integrating with CI/CD tools (Jenkins, GitHub Actions, GitLab CI). Familiarity with distributed computing frameworks (Spark, Ray, TensorFlow Distributed, PyTorch Distributed). Strong understanding of monitoring, logging, and observability for large-scale ML systems. Experience in cost optimisation for compute/GPU workloads. Excellent people ...

Work closely with product and domain experts to translate requirements into robust ML solutions. Who You Are Strong proficiency in Python and experience with PyTorch or TensorFlow . Practical experience with LangChain, LangGraph, AutoGen , or similar LLM/agent frameworks. Skilled in prompt engineering , integrating foundation model APIs ...

Strong experience in Python and SQL, including libraries such as Pandas, NumPy and scikit-learn. Experience working with deep learning frameworks such as PyTorch or TensorFlow. A solid grounding in statistics and probability, with strong mathematical foundations (calculus and linear algebra highly advantageous). Experience working across the full data ...

advanced analytics roles. • Recognised as a technical expert by colleagues, partners and customers. • Strong hands-on knowledge of AI/ML frameworks such as PyTorch, TensorFlow, scikit-learn. • Experience working with cloud AI platforms (AWS, Azure or GCP). • Exposure to private/on-prem AI platforms (e.g. NVIDIA-based ...

forecast key company KPIs, design real-time dashboards, and develop best-in-class data infrastructure. Key Requirements Strong Python (pandas, NumPy, scikit-learn; PyTorch/TensorFlow a plus) and SQL skills Experience applying advanced analytics or ML to real-world data (finance, fintech, or forecasting contexts ideal) Proficiency with ...

reward modelling, RLHF). Hands-on experience training/fine-tuning generative models (LLMs, diffusion, transformers, GANs). Strong knowledge of deep learning frameworks (PyTorch, JAX, TensorFlow). Proficiency in Python and standard ML libraries. Solid foundations in probability, optimisation, and statistics. Experience working with large-scale distributed training ...

Bachelor’s degree 2:1 or above in a quantitative subject). Strong Python skills and experience with ML frameworks (e.g. scikit-learn, TensorFlow, PyTorch). Experience with model deployment, monitoring and ML pipelines (e.g. CI/CD, MLOps concepts). A collaborative mindset with strong communication skills and experience ...

recommendation systems (e.g., semantic embeddings, learning-to-rank, personalisation algorithms). Hands-on experience with modern ML toolchains — Python, Spark, and frameworks such as PyTorch or TensorFlow. Strong grounding in experimental design, A/B testing, and the use of offline/online metrics to guide product strategy. Excellent communication ...