MLOps Engineer

Job Title: MLOps Engineer Company: Valarian Technologies Job Category: Machine Learning Roles & Responsibilities: London Product Development – Engineering / Full time / Hybrid * Scaling open\-weight models without external inference endpoints. * Putting frontier class AI to work across organisations through partnerships with other leading AI startups such as Perplexity. * Increasing operational resiliency for air gapped, on prem, and cloud based systems. * Securing intellectual property and maintaining auditability for high stakes enterprise environments. * Facilitating secure information flow during disaster response, M\&A due diligence, and privileged legal communications. The Role We are looking for an experienced Senior MLOps / LLMOps Engineer to lead the deployment, monitoring, orchestration, and operational reliability of our production LLM applications and agentic AI platform. In this role, you will bridge the gap between AI development and production infrastructure, ensuring multi\-step agentic workflows, data pipelines, and retrieval\-augmented systems run reliably, securely, and at scale within a large\-scale Kubernetes environment. * Design, deploy, and manage LLM services, agentic applications, and supporting AI workloads inside high\-throughput Kubernetes clusters. * Automate containerized deployments, scalable inference endpoints, and blue/green or canary rollout strategies for LLM/Agent releases via modern CI/CD pipelines. * Support and maintain the production operation of agentic AI workflows, including multi\-step tool execution, state management, and multi\-agent coordination. * Rapidly triage and resolve issues across AI application logic, orchestration frameworks, external API integrations, and underlying cloud infrastructure. * Build end\-to\-end monitoring and evaluation (Eval) frameworks to measure and maintain AI output accuracy, drift, latency, cost, and hallucination metrics. * Implement trace\-level observability for agent execution paths (tracking prompts, completions, tool calls, and agent steps). * Monitor and optimize real\-time and batch data pipelines powering AI workloads, including feature stores, vector indexing, and embedding updates. * Manage resource allocation (GPU/CPU utilization), memory footprint, autoscaling strategies, and cloud infrastructure expenditure to optimize time\-to\-first\-token (TTFT) and throughput. What we are looking for: The work we do is vital, but so are the connections that make it happen. We thrive on the shared energy, spontaneous conversations, and mutual trust built when we spend time together. We operate on an office first hybrid model, regularly gathering in our London office to support one another and collaborate. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analyzing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgment. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Work Location: London, ENG, UK Availability: Full time

* 3\+ years of experience in MLOps, LLMOps, Platform Engineering, AI Infrastructure, or SRE with a focus on machine learning workloads. * Hands\-on experience managing and deploying complex containerized applications on Kubernetes (EKS, GKE, AKS, or bare metal) at scale. * Strong proficiency in Python for backend automation, system debugging, custom tooling, and integration development. * Proven experience with standard monitoring/logging tools (e.g., Prometheus, Grafana, Datadog, OpenTelemetry) as well as LLM\-specific tracing and evaluation platforms (e.g., LangSmith, Phoenix/Arize, Langfuse, TruLens). * Familiarity with modern CI/CD pipelines (GitHub Actions, GitLab CI, ArgoCD) and Infrastructure as Code (IaC) tools (Terraform, Pulumi). * Deep operational understanding of agentic architectures, prompt chaining, function calling/tool execution, and non\-deterministic application behavior. Nice to have: Benefits: Our benefits are designed to ensure our employees feel taken care of and are proud to be a part of the Valarian team. We are committed to consistently enhancing our benefit package, taking into account the overall well\-being and needs of our teammates. Here are the key benefits accessible to all employees at Valarian Technologies: * Equity – because you have the right to own what you’re building * A competitive salary – because we value your unique skills * Employer pension contributions – because you deserve a secure future * Private health insurance \- because your health is important to us * Hybrid work setup – because everyone has different needs * Gym memberships \- because staying active fuels productivity * Rewarding company retreats and meetups that respect your work/life balance – because we love getting to know each other Valarian Technologies Limited is an equal opportunity employer and welcomes applications from invdividuals regardless of race, colour, religion, sex, sexual orientation, gender, identity or expression, national origin, age, disability, genetic information, marital status, veteran, amnesty, or any other legally protected characteristic. We are committed to ensuring a fair and inclusive recruitment process and providing employment opportunities to all applicants. Decision recruitment, hiring, and employment are based solely on qualifications, skills, and experience relevant to the job requirements. We may use artificial intelligence (AI) tools to support parts of the hiring process, such as reviewing applications, analysing resumes, or assessing responses and identifying potential inconsistencies or verification signals in application materials based on available information. These tools assist our recruitment team but do not replace human judgement. Final hiring decisions are ultimately made by humans. If you would like more information about how your data is processed, please contact us. Key Skills: Machine Learning, Python Salary: $50