Multiverse is a well-funded 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!
As a MLOps Engineer, you will
Responsible for designing, overseeing and managing end to end machine learning workflow
Develop and implement an MLOps strategy for the organization
Work with development and operations teams to automate Machine Learning product delivery processes
Identify and implement tools and processes to improve data engineering, experiment tracking, model deployment and monitoring for machine learning projects
Actively seek solutions to customer needs, communicate trends to leadership, and suggest innovative solutions on behalf of the customer experience
Help deploy our machine learning models to Fortune 500 clients’ servers
Join a world-class team of Quantum experts with an extensive track record in both academia and industry
Collaborate with the founding team in a fast-paced startup environment
Bachelor’s degree in Computer Engineering, Computer Science, or related field
Alternatively, significant work experience as a Machine Learning Engineer
5+ years of combined experience working as a Machine Learning Engineer and a Data Engineer
Strong programming background with Python
Solid understanding and knowledge of Data Engineering best practices. Hands-on experience required in CI/CD setup for Machine Learning Projects
Strong experience with AWS Services - Sagemaker, AI/ML stack, S3, Lambda, AWS Service APIs, Redshift, Glue, Athena, etc
Experience with AI/ML automation platforms like AWS SageMaker Pipeline, Airflow, Kubeflow, etc
Experience and creativity to design, architect, implement and test complex Infrastructure solutions for machine learning projects
Experience managing machine learning models such as LLMs, CNNs and RNNs from development to deployment
Good communication skills, a great personality, and a love for working collaboratively
Preferred Qualifications
Experience with distributed training/hyperparameter tuning
Experience monitoring and evaluating performance of deployed models
Experience working with different public cloud providers and hybrid environments
Experience in real-time streaming applications
Spain
Multiverse Computing
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