Senior MLOps Engineer (LLMs)

About Multiverse Computing

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!

Position

As a MLOps Engineer, you will

• Deploy 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
• Collaborate with the founding team in a fast-paced startup environment
• 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
• Stay updated with the latest developments in ML/LLM Ops, integrating these advancements into generative AI platforms and processes
• Communicate effectively with both technical and non-technical stakeholders, providing updates on Large Language Model performance and status

Your qualification

• Bachelor's or Master’s degree in Computer Science, Engineering, or a related field
• 5+ years of experience as an ML 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
• Expertise in cloud platforms (e.g., AWS, Azure) for ML workloads, MLOps, DevOps, or Data Engineering
• Solid experience with generative AI applications and domains, including content creation, data augmentation, and style transfer
• Strong understanding of Generative AI architectures and methods, such as chunking, vectorization, context-based retrieval and search, and working with Large Language Models like OpenAI GPT 3.5/4.0, Llama2, Llama3, Mistral, etc
• Proficiency in programming languages such as Python
• Perfect English, Spanish is a plus
• Great communication skills and a love for working collaboratively in an international environment

Preferred Qualifications

• Experience in model parallelism in model training and serving
• Experience with data parallelism/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

What we offer

• Indefinite contract
• Equal pay guaranteed
• Variable performance bonus
• Signing bonus
• We offer work visa sponsorship (If applicable)
• Relocation package (if applicable)
• Private health insurance
• Eligibility for educational budget according to internal policy
• Hybrid opportunity
• Flexible working hours
• Language classes and discounted lunch options
• Working in a high paced environment, working on cutting edge technologies
• Career plan. Opportunity to learn and teach
• Progressive Company. Happy people culture