MLOps/LLMOps Engineer
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A fantastic opportunity for a driven MLOps Engineer to join fast-growing deep-tech company, who provide hyper-efficient software to global companies across finance, energy, manufacturing and cybersecurity to gain an edge with quantum computing and artificial intelligence.
***This is initially a Fixed Term Contract until the end of June 2026, with Hybrid working from a new site in Zaragoza.***
As a MLOps/LLMOps Engineer, you willDeploy cutting-edge ML/LLMs models to Fortune Global 500 clients.Join a world-class team of Quantum experts with an extensive track record in both academia and industry.Design, develop, and implement Machine Learning (ML) and Large Language Model (LLM) pipelines, encompassing data acquisition, preprocessing, model training and tuning, deployment, and monitoring.Employ automation tools such as GitOps, CI/CD pipelines, and containerization technologies (Docker, Kubernetes) to enhance ML/LLM processes throughout the Large Language Model lifecycle.Establish and maintain comprehensive monitoring and alerting systems to track Large Language Model performance, detect data drift, and monitor key metrics, proactively addressing any issues.Conduct truth analysis to evaluate the accuracy and effectiveness of Large Language Model outputs against known, accurate data.Collaborate closely with Product and DevOps teams and Generative AI researchers to optimize model performance and resource utilization.Manage and maintain cloud infrastructure (e.g., AWS, Azure) for Large Language Model workloads, ensuring both cost-efficiency and scalability.Bachelor's or master's degree in computer science, Engineering, or a related field.~1+ years of experience as an ML/LLM engineer in public cloud platforms.~ Proven experience in MLOps, LLMOps, or related roles, with hands-on experience in managing machine/deep learning and large language model pipelines from development to deployment and monitoring.~ Experience in cloud platforms (e.g., AWS, Azure) for ML workloads, MLOps, DevOps, or Data Engineering.~ Knowledge in model parallelism in model training and serving, and data parallelism/hyperparameter tuning.~ Proficiency in programming languages such as Python, distributed computing tools such as Ray, model parallelism frameworks such as DeepSpeed, Fully Sharded Data Parallel (FSDP), or Megatron LM.~ Knowledge in with generative AI applications and domains, including content creation, data augmentation, and style transfer.~ Experience with Azure Machine Learning, Azure Kubernetes Service, Azure CycleCloud, Azure Managed Lustre.~ By applying to this role you understand that we may collect your personal data and store and process it on our systems. xpzdshu
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