advanced machine learning techniques, including graph-based processing, computer vision, natural language processing, and simulation modeling. Experience with generative AI and LLMs, such as LLamaIndex and LangChain Understanding of MLOps or LLMOps. Familiarity with Agile methodologies, preferably Scrum We are actively seeking candidates for full-time, remote work within the UK. More ❯
LLMs) and prompt engineering (e.g., GPT, BERT, T5 family). Familiarity with on-device or edge-AI deployments (e.g., TensorFlow Lite, ONNX, mobile/embedded inference). Knowledge of MLOps tooling (MLflow, Weights & Biases, Kubeflow, or similar) for experiment tracking and model governance. Open-source contributions or published papers in top-tier AI/ML conferences (NeurIPS, ICML, CVPR, ACL More ❯
SQL, BigQuery, noSQL) to programming languages (e.g. R, Python), and from data visualisation (e.g. Tableau, PowerBI) to machine learning. Understanding data engineering solutions is a plus. Strong experience in MLOps, including model lifecycle management, CI/CD for ML, monitoring, and scalable deployment of ML pipelines in production environments Knowledge of CloudOps practices, with expertise in managing scalable, cost-optimized More ❯
PyTorch and TensorFlow, from conception to deployment in scalable environments. Ability to design, deploy, and maintain ML solutions on modern frameworks, adhering to best practices, including version control, testing, MLOps, CI/CD, and API design. Hands-on experience with at least one major cloud platform (AWS, Azure, GCP) in a production setting, and familiarity with ML platforms like AWS More ❯
problem Experience with experiment design and conducting A/B tests Proficiency in Python, with the ability to write production-grade code and a good understanding of data engineering & MLOps Solid understanding of machine learning concepts, familiarity working with common frameworks such as sci-kit-learn, TensorFlow, or PyTorch Collaborative and humble team player with an ability to work with More ❯
delivery , balancing innovation with maintainability, scalability, and performance. Develop and maintain reusable components , APIs, and services that enable rapid deployment of AI features across products. Champion best practices in MLOps and software engineering , including CI/CD, testing, observability, and versioning for AI systems. Mentor and guide junior engineers and cross-functional team members, fostering a culture of technical excellence More ❯
platforms (e.g., B2B SaaS, marketplaces) Background in consulting, research labs, or tech companies with applied ML experience Familiarity with end-to-end ML lifecycle, including model monitoring, retraining, and MLOps best practices Expedia Group is proud to offer a wide range of benefits to support employees and their families, including medical/dental/vision, paid time off, and an More ❯
About Prima Mente Prima Mente's goal is to deeply understand the brain, to protect the brain from neurological disease and enhance the brain in health. We do this by generating our own data, building brain foundation models, and translating More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Opus Recruitment Solutions Ltd
environments (AWS, GCP, or Azure) Ability to work independently and communicate effectively in a remote team Bonus Points Experience with Hugging Face Transformers , LangChain , or RAG pipelines Knowledge of MLOps tools (e.g. MLflow, Weights & Biases, Docker, Kubernetes) Exposure to data engineering or DevOps practices Contributions to open-source AI projects or research publications What We Offer Fully remote working A More ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Method Resourcing
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 data tools (Spark, etc.). Strong written and verbal communication skills, especially More ❯
Mistral. Model performance and optimization: Fine-tuning and optimizing LLMs for quality, latency, sustainability, and cost. Programming and NLP tools: Advanced Python, frameworks like PyTorch, TensorFlow, Hugging Face, LangChain. MLOps and deployment: Docker, Kubernetes, Azure ML Studio, MLFlow. Cloud and AI infrastructure: Experience with Azure Cloud for scalable deployment. Databases and data platforms: SQL, NoSQL, Snowflake, Databricks. OUR VALUES: CURIOSITY More ❯
a customer facing role 2+ years experience in a data-driven role, with exposure to software engineering concepts and best practices (e.g., versioning, testing, CI/CD, API design, MLOps) Building machine learning models and pipelines in Python, using common libraries and frameworks (e.g., TensorFlow, MLFlow) Distributed computing frameworks (e.g., Spark, Dask) Cloud platforms (e.g., AWS, Azure, GCP) and HP More ❯
environment. 3+ years of experience writing production-level code: Routine use and deep understanding of the best practices with version control, unit testing, CI/CD and in general, MLOps for model lifecycle management and monitoring. Familiarity with containerization (Docker) and orchestration for scalable deployment. Ability to write re-usable code What will be your key responsibilities? Plan and lead More ❯
Microsoft Azure AI services. Strong understanding of large language models, prompt engineering, and fine-tuning techniques. Experience with data manipulation libraries (e.g., Pandas, NumPy) and cloud platforms. Familiarity with MLOps, version control (e.g., Git), and deployment tools (e.g., Docker, Kubernetes). Excellent problem-solving skills and the ability to work on complex AI challenges. Nice to Have: Experience with NLP More ❯
using frameworks such as Transformers, PyTorch, or TensorFlow Strong Python skills, with the ability to write clean, modular, production-grade code, and a solid understanding of data engineering and MLOps principles Ability to lead end-to-end ML projects, work independently in ambiguous problem spaces, and mentor junior team members Strong collaboration and communication skills, with experience aligning technical approaches More ❯
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 & Bonus : £35,000 – £45,000 plus bonus 🏡 Hybrid Working : A flexible mix of office and remote work 📈 Career Growth : Structured More ❯
City of London, London, United Kingdom Hybrid / WFH Options
Intellect Group
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 & Bonus : £35,000 – £45,000 plus bonus 🏡 Hybrid Working : A flexible mix of office and remote work 📈 Career Growth : Structured More ❯
5+ years of experience in technical product management Experience working with developer teams and productionizing AI or other data-intensive applications Breadth of knowledge or familiarity with GenAI platforms, MLOps platforms, AI toolkits Deep understanding of software development best practices Organizational and communication skills to effectively coordinate and work with engineers, UX, subject matter experts, other product managers, and senior More ❯
have 5+ years of experience in technical product management Experience working with developerteams and productionizing AI or other data-intensive applications Breadth of knowledge or familiarity with GenAI platforms, MLOps platforms, AI toolkits Deep understanding of software development best practices Organizational and communication skills to effectively coordinate and work with engineers, UX, subject matter experts, other product managers, and senior More ❯
/entity relationships, NoSQL, JSON, XML, SQL and exposure to data visualisation tools (ETL/ELT). Data Science Tools: Proficiency in Numpy, Pandas, Matplotlib, Seaborn and Scikit-learn. MLOps: Experience building pipelines (CI/CD) using Bicep or similar technologies. Expertise in deploying, monitoring and managing machine learning models in production environments. API Development: An understanding of REST. Experience More ❯
models (Hugging Face, PyTorch, TensorFlow) with a strong grounding in evaluating NLP models using classification and ranking metrics, and experience running A/B or offline benchmarks. Proficient with MLOps and training infrastructure (MLflow, Kubeflow, Airflow), including CI/CD, hyperparameter tuning, and model versioning. Strong social media data extraction and scraping skills at scale (Twitter v2, Reddit, Discord, Telegram More ❯
experience in DevOps engineering Solid knowledge of cloud platforms, e.g. Azure/AWS/GCP (mandatory) Mastery of Docker architecture, containerization, and CI/CD tools Proven experience in MLOps practices, integrating machine learning models into scalable, secure production environments is a great plus Comfortable working with Bitbucket, Git, Confluence, and Jira Familiarity with platforms like Databricks is a strong More ❯
small & agile development team focused on building out a greenfield AI-powered transaction monitoring platform. You'll work on everything from ML model development and GenAI summarisation pipelines to MLOps and multi-agent systemswith real-world impact on financial security and compliance. What Youll Do: Develop and deploy machine learning models for anti-money laundering and counter-terrorist financing. Contribute More ❯
teams and mentor junior practitioners Ability to communicate complex technical concepts clearly to non-technical audiences Bonus Points For Participation in Kaggle or other data science competitions Experience with MLOps practices (CI/CD, model monitoring, DevOps integration) Familiarity with advanced NLP frameworks such as spaCy or Transformers MSc or PhD in a numerate discipline Financial services or banking experience More ❯
