Hiring Alert: ML DevOps Engineer Do you want to work at the forefront of robotics innovation? About the company: Extend Robotics is a fast-growing technology company on a mission to scale the world’s labour capacity by extending human capabilities beyond physical presence. We are a special group of ambitious individuals from around the world to solve problems with first principle and world class technology. We put human in the centre of technologies, and passionate about metaverse, robotics and artificial intelligence. This is a unique opportunity to be part of the biggest revolution of humanity. We work at extremely fast pace and offer a friendly working environment, encouraging innovative ideas and work on a world-leading technology products and services. We have an exciting opening for an ML DevOps Engineer to work closely with our R&D and Product teams. You will play a key role in delivering efficient data flywheel to fuel the next-generation robotic software designed to automate tasks via intuitive, human-in-the-loop interfaces. We focus on outcomes that solve real needs for our partners and customers. We also offer a friendly and flexible working environment, freedom to explore ideas and work on a world-leading robotics products and services. ________________________________________ About the job: Model Deployment & Pipeline Automation: Designing, building, and maintaining automated, end-to-end CI/CD pipelines for training, testing, and deploying ML model Maintain analytical tools for production monitoring: Continuously tracking model performance, accuracy, and latency, and detecting data drift or concept drift in production. Infrastructure Management: Provisioning and optimizing cloud (AWS, GCP, Azure) or on-premises infrastructure, including containerization (Docker, Kubernetes) to ensure scalable workloads. Develop and maintain user portal frontend live fleet configuration, monitoring and management dashboard Data Engineering: Collaborating with data engineers to manage data ingestion, preprocessing, and feature stores (e.g., storing, accessing, and defining features for training). Version Control & Governance: Implementing version control for models, data, and code to ensure reproducibility and compliance with security standards (e.g., GDPR, HIPAA). Collaboration: Working with data scientists to transition models from notebooks to production-grade, API-driven services. About the candidate: Experience: 3–7 years of experience in MLOps, machine learning engineering, or software engineering/DevOps roles. Programming: Proficient in Python (crucial for automation) and shell scripting (Bash). ML Frameworks: Familiarity with TensorFlow, PyTorch, or Scikit-learn. DevOps & Cloud: Experience with cloud platforms (AWS SageMaker, Azure ML, Vertex AI) and infrastructure-as-code (Terraform, CloudFormation). Containers & Orchestration: Strong expertise in Docker and Kubernetes. MLOps Tooling: Experience with tools like MLflow (tracking), Kubeflow (pipelines), Apache Airflow (orchestration), or DVC (data versioning). Education: Bachelor’s or Master’s degree in Computer Science, Data Science, or a related field. Soft Skills: Strong problem-solving, collaboration, and communication skills to work across cross-functional teams. ________________________________________ Benefits and advantages offered to successful candidates: Welcoming and nurturing work atmosphere Comprehensive orientation program for both corporate and technical aspects Attractive compensation package Exciting opportunity to participate in our Share Option Scheme after one year of service. Generous annual leave of 25 days, in addition to bank holidays Start date: March/April 2026 Term: Full-time employment Location: Reading, United Kingdom (on-site)