managing ML models in production, in Azure Databricks. Tech stack: Databricks, Unity Catalog, Python, Git, MLFlow, Delta tables, Azure DevOps. Hands-on development experience using Python, particularly with TensorFlow, PyTorch, scikit-learn, boto3, and the Python Data Science stack (pandas, numpy, etc.). Strong analytical and problem-solving skills, with the ability to work with large-scale, complex datasets. Experience More ❯
degree (or equivalent) in Computer Science, Machine Learning, or a related field. 3+ years of experience deploying ML models in production. Proficient in Python and ML frameworks (e.g., TensorFlow, PyTorch). Experience working with cloud platforms and containerised deployments (e.g., Docker, Kubernetes). Solid grounding in computer vision and experience with large-scale data. Bonus: exposure to reinforcement learning methods. More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Brio Digital
degree (or equivalent) in Computer Science, Machine Learning, or a related field. 3+ years of experience deploying ML models in production. Proficient in Python and ML frameworks (e.g., TensorFlow, PyTorch). Experience working with cloud platforms and containerised deployments (e.g., Docker, Kubernetes). Solid grounding in computer vision and experience with large-scale data. Bonus: exposure to reinforcement learning methods. More ❯
Hands on experience working within areas such as NLP, LLM, recommendation systems Information Retrieval stacks, GenAI (specifically RAG systems). Familiar with architecture and implementation of 1+ ML frameworks (PyTorch, scikit-learn). Experience working in the full model lifecycle (including experimentation, training, testing, monitoring, and deployment). Good knowledge of AWS’s machine learning infrastructure. Again this is a More ❯
South East London, England, United Kingdom Hybrid / WFH Options
Brio Digital
degree (or equivalent) in Computer Science, Machine Learning, or a related field. 3+ years of experience deploying ML models in production. Proficient in Python and ML frameworks (e.g., TensorFlow, PyTorch). Experience working with cloud platforms and containerised deployments (e.g., Docker, Kubernetes). Solid grounding in computer vision and experience with large-scale data. Bonus: exposure to reinforcement learning methods. More ❯
e.g., Triton, TensorRT, TorchServe). Experience with GPU scaling for large-scale machine learning models. Expertise in deploying complex machine learning pipelines in production environments. Desirable Skills: Proficiency with PyTorch and Hugging Face transformers. Experience with neural audio codecs (e.g., Encodec). Background in Text-to-Speech (TTS) development. Experience with advanced techniques such as Residual Vector Quantization (RVQ), Generative More ❯
practical solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Proficiency in Python, SQL, and AI/ML frameworks such as PyTorch and TensorFlow. Ability to address model hallucination, optimize performance, and oversee governance around AI risk and ethics. Ready to Transform the Future? This is a career-defining opportunity within a More ❯
solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Highly proficient in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow). Ability to mitigate model hallucination, optimise performance, and lead governance around AI risk and ethical deployment. Ready to Transform the Future? This a career-defining opportunity working within More ❯
Better Placed Ltd - A Sunday Times Top 10 Employer!
practices, including model versioning, CI/CD pipelines, containerization, and cloud deployment for large-scale models. Solid programming skills in Python and familiarity with machine learning frameworks like TensorFlow, PyTorch, Hugging Face Transformers, and MLOps tools (e.g., MLflow, Kubeflow). Strong analytical and problem-solving skills, with an aptitude for translating complex theoretical research into practical applications. Day to Day More ❯
Integration: Build APIs (FastAPI, Flask) and integrate with React, TypeScript, Node.js Required skills & experience: 3–5+ years of experience in ML engineering and software development Deep Python proficiency, with PyTorch, TensorFlow or Hugging Face Proven experience with LLMs, RAG, and deploying cloud-native AI on AWS Strong full-stack skills (React, TypeScript, Node.js) and API development Familiarity with vector databases More ❯
image and 3D data. Your strong programming skills in Python and/or Modern C++ will be invaluable in this role. Experience with libraries such as OpenCV, Open3D, Tensorflow, PyTorch is a must. Above all, your ambition and hunger for growth and development will drive you to excel in this role. Masters in Machine Learning/Computer Vision/Geometry More ❯
solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Highly proficient in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow). Ability to mitigate model hallucination, optimise performance, and lead governance around AI risk and ethical deployment. Ready to Transform the Future? This a career-defining opportunity working within More ❯
solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Highly proficient in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow). Ability to mitigate model hallucination, optimise performance, and lead governance around AI risk and ethical deployment. Ready to Transform the Future? This a career-defining opportunity working within More ❯
or a quantitative academic field. Strong Python programming skills demonstrated through prior work. Proficiency with data science libraries (NumPy, Pandas, Scikit-Learn) and familiarity with deep learning frameworks (TensorFlow, PyTorch). High mathematical competence and statistical proficiency. Knowledge of standard data science techniques and ability to develop new algorithms. Understanding of the scientific method in a business context, with problem More ❯
NLP, Information Retrieval, or Conversational AI Experience with large language models and retrieval-augmented generation Research background in conversational systems or dialogue management Experience with modern deep learning frameworks (PyTorch, TensorFlow) Excellent written and verbal communication skills PREFERRED QUALIFICATIONS Knowledge of multi-agent systems and tool-use frameworks Experience with e-commerce or shopping domain applications Publications at top venues More ❯
business solutions. Strong engineering fundamentals, including DevOps, CI/CD, and secure ML/AI pipelines (DevSecOps). Proficiency in Python, SQL, and key AI/ML frameworks (e.g., PyTorch, TensorFlow). Ability to mitigate model hallucination, optimize performance, and lead governance around AI risk and ethical deployment. Ready to Transform the Future? This is a career-defining opportunity within More ❯
Proven experience leading the development, deployment, and lifecycle management of complex ML systems. Strong programming skills in Python and potentially R. Expertise with relevant ML frameworks (e.g., scikit-learn, PyTorch). Experience with recommendation systems, collaborative filtering, and ideally Graph Neural Networks (GNNs). Proficient with SQL and working with large datasets (e.g., GCP BigQuery). Experience with cloud platforms More ❯
AWS/GCP/Azure) and infrastructure as code Experience with monitoring and observability tools Background in financial technology or capital markets Understanding of basic ML concepts and frameworks (PyTorch, TensorFlow) You: Are passionate about building robust, scalable systems that solve real-world problems Have a growth mindset and enjoy learning new technologies and domains Can communicate complex technical concepts More ❯
model deployment, monitoring, versioning, and continuous improvement frameworks (MLflow, AWS SageMaker Model Monitor), ensuring models meet scalability, latency, and operational performance requirements. Have experience with deep learning frameworks (TensorFlow, PyTorch), AWS SageMaker, Bedrock, Lambda, and familiarity with Azure AI Foundry is advantageous. Be familiar with software engineering best practices (version control, CI/CD, code reviews), with some exposure to More ❯
for in Research Engineers are: Degree in computer science, electrical engineering, science, mathematics or equivalent experience. Extensive software engineering experience, particularly with Python-based scientific libraries such as JAX, PyTorch, TensorFlow, NumPy. Familiarity with machine learning and RL, plus the mathematics and statistics knowledge needed to follow relevant research papers (linear algebra, calculus, etc). We're also interested in More ❯
using deep learning techniques, including designing new architectures, hands-on experimentation, analysis, and visualisation. Strong knowledge of linear algebra, calculus and statistics. Experience using ML frameworks such as JAX, PyTorch, or TensorFlow, and scientific software such as NumPy, SciPy, or Pandas. A passion for applying ML research to real world problems. Depending on your experience: project supervision, leadership, or management. More ❯
Hands-on experience with MLOps and AIOps infrastructure and tooling. Proficient in problem-solving and analytical reasoning. Exceptional communication and collaboration skills. Experience with ML frameworks such as TensorFlow, PyTorch, TensorRT, or ONNX. Experience with Large Language Models, including RAG and fine-tuning techniques. Familiarity with compute infrastructure necessary to support operating AI and ML technology. More ❯
Face Transformers, OpenAI API, LangChain, or similar Experience fine-tuning large transformer models or implementing retrieval-augmented generation systems Strong Python programming skills and familiarity with ML libraries (e.g., PyTorch, TensorFlow) Knowledge of prompt engineering best practices and prompt optimization Understanding of LLM evaluation methods, including human-in-the-loop and automated metrics Familiarity with deploying LLMs in cloud or More ❯
Machine Learning engines (AWS, Azure, Google, etc.) Experiencewith large scale data processing tools (Spark, Hadoop, etc.) Abilityto query and program databases (SQL, No SQL) Experiencewith distributed ML frameworks (TensorFlow, PyTorch, etc.) Familiaritywith collaborative software tools (Git, Jira, etc.) Experiencewith user interface libraries/applications (Shiny, Django, etc.) Experiencein developing ML or statistical models in the field of pricing (e.g. priceelasticity More ❯
