Senior MLOps Engineer (Training & Inference Optimization)

Technical · San Sebastian, Spain

Multiverse Computing

Multiverse is a well-founded and fast-growing deep-tech company founded in 2019. We are one of the few companies working with Quantum Computing and the biggest Quantum Software company in the EU.

We provide hyper-efficient software to companies wanting to gain an edge with quantum computing and artificial intelligence. Our product, Singularity, is a software platform that contains quantum and quantum-inspired algorithms developed and patented through proof-of-concept trials we have been performing for industrial and service clients. We work in finance, energy, manufacturing, cybersecurity and many more industries.

You will be working alongside world leading experts to build solutions that tackle real life issues. We look for passionate people that want to grow in an ethics driven environment, promoting sustainability and diversity. We aim to continue building our truly inclusive culture - come and join us!

About the Role

We are seeking a Senior MLOps Engineer specializing in training and inference optimization. This role focuses on optimizing machine learning workflows, improving model performance, and ensuring efficient deployment and inference of large-scale AI models.

Responsibilities

• Optimize ML training pipelines for performance, cost, and resource efficiency

• Develop and maintain tools for distributed training and inference

• Build monitoring and observability solutions for ML systems

• Optimize model inference for production environments

• Collaborate with ML researchers and software engineers to implement best practices

• Implement CI/CD pipelines specifically for ML models and data workflows

• Research and evaluate new tools and techniques for model optimization

• Mentor junior engineers on MLOps best practices

What we are looking for:

• 6+ years of experience in machine learning operations or data engineering

• 3+ years hands-on experience with large language models (LLMs) or transformer-based models

• Strong proficiency in Python and deep learning frameworks (PyTorch, TensorFlow)

• Experience with distributed training (PyTorch Distributed, Horovod, DeepSpeed)

• Knowledge of model optimization techniques (quantization, pruning, distillation)

• Experience with ML platforms and tools (MLflow, Kubeflow, Weights & Biases)

• Strong understanding of cloud infrastructure and containerization (Docker, Kubernetes)

• Experience with GPU/TPU management and optimization

• Bachelor's degree in Computer Science or equivalent professional experience

What we offer:

• Competitive salary (€65,000 - €85,000 annually based on experience)

• Stock options in a well-funded deep-tech company

• Flexible work arrangements (hybrid model)

• Professional development budget and training opportunities

• Health insurance and retirement benefits

• International, collaborative team environment

• Direct impact on quantum computing and AI solutions

If you're passionate about optimizing ML systems and working with cutting-edge technologies, we'd love to hear from you.