MLOps Engineer (Fixed term contract) | Relocation Offered

Job description

Join to apply for the

MLOps Engineer (Fixed-term contract) | Relocation Offered

role at

Relocate.me About Multiverse Computing Multiverse is a well-funded, fast-growing deep-tech company founded in 2019.

We are the largest quantum software company in the EU and have been recognized by CB Insights (2023 and 2025) as one of the 100 most promising AI companies in the world.

About Multiverse Computing With 180+ employees and growing, our team is fully multicultural and international.

We deliver hyper-efficient software for companies seeking a competitive edge through quantum computing and artificial intelligence.

Our flagship products, CompactifAI and Singularity, address critical needs across various industries: CompactifAI is a groundbreaking compression tool for foundational AI models based on Tensor Networks.

It enables the compression of large AI systems—such as language models—to make them significantly more efficient and portable.

Singularity is a quantum- and quantum-inspired optimization platform used by blue-chip companies to solve complex problems in finance, energy, manufacturing, and beyond.

It integrates seamlessly with existing systems and delivers immediate performance gains on classical and quantum hardware.

We’re looking for passionate individuals eager to grow in an ethics-driven environment that values sustainability and diversity.

We’re committed to building an inclusive culture—come and join us.

Position We are looking to fill this role immediately and are reviewing applications daily.

Expect a fast, transparent process with quick feedback.

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.

Mid or Senior: 3+ 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.

Expertise in cloud platforms (e.g., AWS, Azure) for ML workloads, MLOps, DevOps, or Data Engineering.

Expertise 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.

Expertise in 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.

Experience with Azure Machine Learning, Azure Kubernetes Service, Azure CycleCloud, Azure Managed Lustre.

Experience with English fluency; Spanish is a plus.

Great communication skills and a passion for working collaboratively in an international environment.

Will be a plus

Experience in training “Mixture-of-Experts Experience working with different public cloud providers and hybrid environments.

Experience in real-time streaming applications.

Experience with training pipeline optimization, inference optimization, LLM observability and LLM API management What we offer

Competitive annual salary starting from €55,000, based on experience and qualifications.

Two unique bonuses: signing bonus at incorporation and retention bonus at contract completion.

Relocation package (if applicable).

Fixed-term contract ending in June 2026.

Hybrid role and flexible working hours.

Be part of a fast-scaling Series B company at the forefront of deep tech.

Equal pay guaranteed.

International exposure in a multicultural, cutting-edge environment.

Additional details

As an equal opportunity employer, Multiverse Computing is committed to building an inclusive workplace.

The company welcomes people from all different backgrounds, including age, citizenship, ethnic and racial origins, gender identities, individuals with disabilities, marital status, religions and ideologies, and sexual orientations to apply.

Engineer Developer Programmer DevOps AWS Amazon Cloud Data Engineer ML Azure Machine Learning MLOps LLM Amazon Web Services Data Engineering sql-azure MLOps engineer Multiverse Computing Seniority level

Mid-Senior level Employment type

Full-time Job function

Engineering and Information Technology Industries

Technology, Information and Internet We’re unlocking community knowledge in a new way.

Experts add insights directly into each article, started with the help of AI.

#J-18808-Ljbffr

Required Skill Profession

Ingeniería Y Tecnología