based workflows. Strong problem-solving mindset and a proactive approach to automation and scaling. Ability to communicate clearly and collaborate across cross-functional teams. Nice to Have Familiarity with MLOps tools such as MLflow, DVC, Airflow, or Kubeflow. Experience working with large language models or other Generative AI tools. Exposure to agentic AI concepts and implementations. Knowledge of cloud infrastructure 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 ❯
or Azure SQL Database is beneficial. Experience in designing and maintaining robust CI/CD pipelines, applying Infrastructure as Code (IaC) principles with exposure to Terraform, and incorporating Azure MLOps practices for seamless deployment, versioning, and traceability of AI models and data Knowledge of DevSecOps principles and data governance best practices to secure AI infrastructure and ensure compliance. The ability More ❯
or Azure SQL Database is beneficial. Experience in designing and maintaining robust CI/CD pipelines, applying Infrastructure as Code (IaC) principles with exposure to Terraform, and incorporating Azure MLOps practices for seamless deployment, versioning, and traceability of AI models and data Knowledge of DevSecOps principles and data governance best practices to secure AI infrastructure and ensure compliance. The ability More ❯
or Azure SQL Database is beneficial. Experience in designing and maintaining robust CI/CD pipelines, applying Infrastructure as Code (IaC) principles with exposure to Terraform, and incorporating Azure MLOps practices for seamless deployment, versioning, and traceability of AI models and data Knowledge of DevSecOps principles and data governance best practices to secure AI infrastructure and ensure compliance. The ability 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 ❯
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 ❯
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 ❯
platforms such as OpenAI on Azure, AWS Bedrock, GCP Vertex AI, or Gemini AI. Architecture & Deployment: Designing, deploying, and scaling AI architectures aligned to enterprise standards. Proven experience in MLOps and AI lifecycle management, with scalable deployments across AWS, GCP, and Azure. Bridging business and technical teams, owning high- and low-level design for services, products, and solutions. Optimizing solutions More ❯
will support your career growth with us. Experience in programming in multiple languages, including Java, JavaScript and Python. Knowledge of and exposure to coaching frameworks. Hands-on experience with MLOps, data engineering, or deployment of AI/ML models (real time and batch) in a business environment. Experience leading teams on AI-driven projects, such as recommendation systems, automation, or More ❯
managing business-critical machine learning models using Azure ML in Production environments. Experience in data wrangling using Python, SQL and ADF. Experience in CI/CD and DevOps/MLOps and version control. Familiarity with data visualization and reporting tools, ideally PowerBI. Good written and verbal communication and interpersonal skills. Ability to convey technical concepts to non-technical stakeholders. Experience More ❯
be instrumental in designing and optimising our analytics architecture, transforming complex raw data into highly reliable, well-documented datasets. These datasets will serve as the foundation for advanced analytics, MLOps, self-serve capabilities, and strategic decision-making across the business. You will collaborate with our Data Manager, Data Engineer, Analysts, and business stakeholders, building the scalable data pipelines and semantic More ❯
Demonstrated ability to build relationships with stakeholders and subject matter experts. Familiarity with high compute cloud-based platforms and services, in particular AWS. Familiarity with code version control and MLOps deployment approaches. Minimum Requirements Advanced degree (MS or PhD) in Data Science, Computer Science, Biostatistics, or related field 3 - 5 years of related professional experience, with 1+ years of experience More ❯
Demonstrated ability to build relationships with stakeholders and subject matter experts. Familiarity with high compute cloud-based platforms and services, in particular AWS. Familiarity with code version control and MLOps deployment approaches. Ability to understand healthcare challenges and adapt accordingly the AI solutions. Cross-functions high adaptability to meet cross organization goals. Required/Preferred Education Advanced degree (MS or More ❯
tools Proven experience building and deploying agentic AI systems , multi-agent frameworks , or LLM-powered automation Strong grasp of prompt engineering , RAG pipelines , and autonomous task execution Familiarity with MLOps , cloud platforms (AWS/GCP/Azure), and AI infrastructure pipelines Excellent communication and stakeholder engagement skills—client-facing experience essential 🌍 Why Apply? ✅ Global Reach : Collaborate with world-leading brands More ❯
knowledge of Python, R, and Java. Experience scaling machine learning on data and compute grids. Proficiency with Kubernetes, Docker, Linux, and cloud computing. Experience with Dask, Airflow, and MLflow. MLOps, CI, Git, and Agile processes. Why you do not want to miss this career opportunity? We are a mission-driven firm that is revolutionising the Insurance and Banking industry. We More ❯
leads who are spread across several geographies. The team covers a variety of industries, functions, analytics methodologies and platforms – e.g. Cloud data engineering, advanced statistics, machine learning, predictive analytics, MLOps and generative AI. What You’ll Do You will collaborate closely with a team comprising data scientists, data engineers, product developers, and analytics-focused consultants. As a data savvy Business More ❯
leads who are spread across several geographies. The team covers a variety of industries, functions, analytics methodologies and platforms – e.g. Cloud data engineering, advanced statistics, machine learning, predictive analytics, MLOps and generative AI. What You’ll Do You will collaborate closely with a team comprising data scientists, data engineers, product developers, and analytics-focused consultants. As a data savvy Business More ❯
Demonstrated ability to build relationships with stakeholders and subject matter experts. Familiarity with high compute cloud-based platforms and services, in particular AWS. Familiarity with code version control and MLOps deployment approaches. Minimum Requirements Advanced degree (MS or PhD) in Data Science, Computer Science, Biostatistics, or related field 3 5 years of related professional experience, with 1+ years of experience More ❯
