Lead MLOps Engineer
<p><b>Salary: £100,000 - 100,000 per year</b></p>
<b>Requirements:</b>
<ul><li>Staff or lead-level experience in MLOps, DevOps, or Infrastructure Engineering, ideally within high-growth or startup environments</li><li>Strong Python skills with hands-on experience using modern ML frameworks (e.g., PyTorch, TensorFlow, or similar)</li><li>Experience working with major cloud platforms (AWS, GCP, or Azure)</li><li>Proven production experience with Docker and Kubernetes</li><li>Strong understanding of CI/CD systems (e.g., GitHub Actions, GitLab CI, ArgoCD)</li><li>Experience with Infrastructure as Code tools such as Terraform and Helm</li><li>Solid understanding of data engineering fundamentals and ML lifecycle management</li><li>Ability to design scalable systems without unnecessary complexity</li><li>Strong debugging and problem-solving skills in distributed systems</li><li>Ownership mindset with excellent communication and cross-functional collaboration skills</li></ul>
<b>Responsibilities:</b>
<ul><li>Own and scale the organisations ML infrastructure and MLOps foundations</li><li>Design pragmatic, production-ready system architectures that balance speed, reliability, and cost</li><li>Build and maintain CI/CD pipelines for ML workflows and application delivery</li><li>Productionise ML models including training, evaluation, deployment, monitoring, and rollback strategies</li><li>Ensure reliability, observability, security, and performance across ML systems</li><li>Automate infrastructure provisioning, deployments, and environment management using cloud-native tooling</li><li>Partner closely with ML engineers, software engineers, and product teams to deliver ML features end-to-end</li><li>Act as a technical leader through design reviews, mentorship, and by establishing engineering best practices</li></ul>
<b>Technologies:</b>
<ul><li>AI</li><li>AWS</li><li>ArgoCD</li><li>Azure</li><li>CI/CD</li><li>Cloud</li><li>DevOps</li><li>Docker</li><li>GCP</li><li>GitHub</li><li>GitLab</li><li>Helm</li><li>Kubernetes</li><li>PyTorch</li><li>Python</li><li>Robotics</li><li>Security</li><li>TensorFlow</li><li>Terraform</li><li>Machine Learning</li></ul>
<p><b>More:</b></p>
<p>We are a fast-growing AI and robotics organization focused on building advanced, scalable intelligent systems for real-world industrial applications. This high-impact role offers a competitive salary, equity participation, and paid vacation in line with local labor regulations. Additionally, we provide opportunities for international collaboration and travel, along with office benefits including meals, snacks, and team events. We welcome candidates willing to relocate to London as we can help facilitate this move.</p>
<p>last updated 8 week of 2026</p>
<b>Requirements:</b>
<ul><li>Staff or lead-level experience in MLOps, DevOps, or Infrastructure Engineering, ideally within high-growth or startup environments</li><li>Strong Python skills with hands-on experience using modern ML frameworks (e.g., PyTorch, TensorFlow, or similar)</li><li>Experience working with major cloud platforms (AWS, GCP, or Azure)</li><li>Proven production experience with Docker and Kubernetes</li><li>Strong understanding of CI/CD systems (e.g., GitHub Actions, GitLab CI, ArgoCD)</li><li>Experience with Infrastructure as Code tools such as Terraform and Helm</li><li>Solid understanding of data engineering fundamentals and ML lifecycle management</li><li>Ability to design scalable systems without unnecessary complexity</li><li>Strong debugging and problem-solving skills in distributed systems</li><li>Ownership mindset with excellent communication and cross-functional collaboration skills</li></ul>
<b>Responsibilities:</b>
<ul><li>Own and scale the organisations ML infrastructure and MLOps foundations</li><li>Design pragmatic, production-ready system architectures that balance speed, reliability, and cost</li><li>Build and maintain CI/CD pipelines for ML workflows and application delivery</li><li>Productionise ML models including training, evaluation, deployment, monitoring, and rollback strategies</li><li>Ensure reliability, observability, security, and performance across ML systems</li><li>Automate infrastructure provisioning, deployments, and environment management using cloud-native tooling</li><li>Partner closely with ML engineers, software engineers, and product teams to deliver ML features end-to-end</li><li>Act as a technical leader through design reviews, mentorship, and by establishing engineering best practices</li></ul>
<b>Technologies:</b>
<ul><li>AI</li><li>AWS</li><li>ArgoCD</li><li>Azure</li><li>CI/CD</li><li>Cloud</li><li>DevOps</li><li>Docker</li><li>GCP</li><li>GitHub</li><li>GitLab</li><li>Helm</li><li>Kubernetes</li><li>PyTorch</li><li>Python</li><li>Robotics</li><li>Security</li><li>TensorFlow</li><li>Terraform</li><li>Machine Learning</li></ul>
<p><b>More:</b></p>
<p>We are a fast-growing AI and robotics organization focused on building advanced, scalable intelligent systems for real-world industrial applications. This high-impact role offers a competitive salary, equity participation, and paid vacation in line with local labor regulations. Additionally, we provide opportunities for international collaboration and travel, along with office benefits including meals, snacks, and team events. We welcome candidates willing to relocate to London as we can help facilitate this move.</p>
<p>last updated 8 week of 2026</p>