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 ❯
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 ❯
/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 ❯
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 ❯
scalable systems and high-volume, low latency, transaction/computation applications. Broad understanding of the software development lifecycle, including the application of LLM driven and Data Science DevOps/MLOps/AIOps methodologies. Expertise in data management and analytics, including data structures, data processing, data modelling, and statistical analysis. Knowledge of Python and C# for development and scripting. Leadership: Proven More ❯
scalable systems and high-volume, low latency, transaction/computation applications. Broad understanding of the software development lifecycle, including the application of LLM driven and Data Science DevOps/MLOps/AIOps methodologies. Expertise in data management and analytics, including data structures, data processing, data modelling, and statistical analysis. Knowledge of Python and C# for development and scripting. Leadership: Proven 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 ❯
translate technical work into business outcomes and influence stakeholders at all levels. Extra Awesome Experience managing hybrid teams that include both Data Scientists and ML Engineers Exposure to modern MLOps tooling (e.g. MLflow, Feature Store, SageMaker, Vertex AI) Familiarity with unstructured data modeling (e.g. NLP, embeddings, LLMs) and GenAI product patterns Experience working in product-led or B2B SaaS environments More ❯
organizations. You have experience developing state-of-the-art deep learning models, LLMs, and advanced AI architectures . You are an industry expert in ML model development, deployment, and MLOps at scale . You are deeply comfortable with Python, SQL, and ML frameworks (e.g., TensorFlow, PyTorch) and have experience working in a microservices architecture (Go Lang experience is a plus 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 ❯
London, South East, England, United Kingdom Hybrid / WFH Options
Salt Search
working in B2C, e-commerce, subscription, retail, or fintech industries is a strong advantage Nice to Have Experience with NLP for customer feedback or support ticket analysis Exposure to MLOps for model deployment and monitoring Familiarity with tools like Amplitude, Mixpanel, or Google Analytics Why Join Us? Shape data-driven strategy for how we understand and engage with our customers More ❯
working in B2C, e-commerce, subscription, retail, or fintech industries is a strong advantage Nice to Have Experience with NLP for customer feedback or support ticket analysis Exposure to MLOps for model deployment and monitoring Familiarity with tools like Amplitude, Mixpanel, or Google Analytics Why Join Us? Shape data-driven strategy for how we understand and engage with our customers More ❯
Actions, ArgoCD) Ability to lead delivery in agile environmentsbalancing scope, prioritisation, and quality Excellent communication and collaboration skills across technical and non-technical stakeholders A background in software engineering, MLOps, or data engineering with production ML experience Nice to have: Familiarity with streaming or event-driven ML architectures (e.g. Kafka, Flink, Spark Structured Streaming) Experience working in regulated domains such More ❯
machine learning solutions for performance and scalability. Custom Code: Implement tailored machine learning code to meet specific needs. Data Engineering: Ensure efficient data flow between databases and backend systems. MLOps : Automate ML workflows, focusing on testing, reproducibility, and feature/metadata storage. ML Architecture Design: Create machine learning architectures using Google Cloud tools and services. Engineering Software for Production: Build More ❯
marketing performance managers. Experience in Python and SQL. Experience with cloud platforms such as Amazon Web Services, Azure, or Google Cloud Platform. Deep understanding of Generative AI, NLP, and MLOps concepts. Analytical, flexible, independent, and a strong communicator. WE OFFER: A flexible, hybrid working policy (2 days from the office, depending on location). An excellent salary based on experience More ❯
driven decision-making process, from data collection and analysis to implementation and monitoring of solutions facilitate adoption of ML models through exceptional communication with stakeholders work in an established MLOps team at SB there is significant opportunity to deploy end to end and will be actively encouraged continually improve through active learning and development highlighting opportunities for SB to stay More ❯
Nice to have Experience building Data Mesh or Data Lake architectures. Familiarity with Kubernetes, Docker, and real-time streaming (e.g. Kafka, Kinesis). Exposure to ML engineering pipelines or MLOps frameworks. What's it like to work at Zego? Joining Zego is a career-defining move. People go further here, reaching their full potential to achieve extraordinary things. We're More ❯
Nice to have Experience building Data Mesh or Data Lake architectures. Familiarity with Kubernetes, Docker, and real-time streaming (e.g. Kafka, Kinesis). Exposure to ML engineering pipelines or MLOps frameworks. Whats it like to work at Zego? Joining Zego is a career-defining move. People go further here, reaching their full potential to achieve extraordinary things. We're spread More ❯
