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MCMultiverse Computing
Multiverse ComputingDeep-tech AI

MLOps Engineer

Location

Multiple, Global

Work type

Hybrid

Employment

Full Time

Experience

2-5 years

Compensation

Compensation not disclosed

Posted

1h ago

Summary and responsibilities

Role overview

Summary

As an MLOps Engineer, you will be responsible for deploying cutting-edge ML/LLM models to clients and designing, developing, and implementing ML/LLM pipelines. This role involves employing automation tools, establishing monitoring systems, and collaborating with various teams to optimize model performance and resource utilization.

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.

Required Qualification

  • Bachelor's or master's degree in computer science, Engineering, or a related field.

  • Mid - 2+ years of experience as an ML/LLM engineer in public cloud platforms.

  • Senior - 5+ 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 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.

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

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

Preferred Qualifications

  • Experience in training “Mixture-of-Experts

Updated 1h ago

Candidate fit

Skills and qualifications

Additional skills

MLOps • 1+ yrs
LLMOps • 1+ yrs
Machine Learning • 1+ yrs
Large Language Models • 1+ yrs
Generative AI • 1+ yrs
Python • 1+ yrs
Docker • 1+ yrs
Kubernetes • 1+ yrs

Experience

2-5 years

How this role is positioned

Role classification

Job domains

IT & System Administration
Software Engineering

Industries

Technology & IT
Finance & Banking

Employment

Full Time

Contract duration

Permanent

Hiring type

Direct

Global hiring

Location specific

Offer details

Compensation and benefits

Compensation

Compensation not disclosed

VisibilityShared on listing
CurrencyUSD
PeriodYearly

Benefits and perks

Performance Bonus
Signing Bonus
Visa Sponsorship
Health Insurance
Flexible Working Hours

Location, schedule, and role shape

Work setup

Work conditions

Primary locationMultiple, Global
Work typeHybrid
Global hiringNo

Bandwidth profile

peopleHigh8/10
physicalLow2/10
cognitiveHigh9/10
executionHigh8/10
creativityMedium7/10
uncertaintyMedium7/10
communicationHigh8/10

Context on the employer

Company snapshot

Company

Multiverse Computing

Team size

Growing team

Location

Multiple, Global

Multiverse is a 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. 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.

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MLOps Engineer

Multiple, GlobalFull Time