AI SCORE 8.5

MLOps Engineer - AI Start-up

$90K–$110K/year

About the Role

We are seeking an experienced MLOps Engineer to join our innovative AI start-up. This MLOps Engineer remote position allows you to work flexibly while contributing to groundbreaking technology that is transforming the AI landscape. You will be part of a dynamic team that is compressing large language models by up to 95% and significantly reducing inference costs. This is your opportunity to be part of a company often referred to as a “quantum-AI unicorn in the making.”

What You'll Do

  • Design, deploy, and monitor end-to-end ML/LLM pipelines, ensuring smooth data acquisition to production.
  • Scale cloud infrastructure on AWS or Azure using GitOps, CI/CD, Docker, and Kubernetes.
  • Collaborate with AI researchers to optimize model performance and resource utilization.
  • Stay updated with the latest advancements in LLMOps and integrate generative AI innovations.
  • Bridge the gap between technical and non-technical stakeholders through effective communication.

Requirements

  • 3+ years of experience in MLOps/LLMOps within public cloud environments (AWS/Azure).
  • Expertise in model/data parallelism, hyperparameter tuning, and frameworks such as DeepSpeed, FSDP, Ray, or Megatron-LM.
  • Strong understanding of RAG (chunking, vectorization) and LLMs (GPT-4, Llama 3, Mistral).
  • Hands-on experience with Azure ML, AKS, CycleCloud, and Managed Lustre.
  • Fluent in English; Spanish is a plus.
  • Bachelor’s degree in Computer Science, Engineering, or a related field.

Nice to Have

  • Experience in a fast-scaling company environment.
  • Familiarity with diverse and inclusive workplace cultures.

What We Offer

  • Competitive salary with a signing bonus and retention bonus.
  • Flexible working hours and a hybrid work model.
  • Relocation package available if needed.
  • International exposure in a multicultural environment.
  • Commitment to equal pay, diversity, and an inclusive culture.

If you are interested in this MLOps Engineer remote opportunity, apply directly through LinkedIn or send your CV to george@eu-recruit.com. By applying to this role, you understand that we may collect your personal data and store and process it on our systems. For more information, please see our Privacy Notice.

Language Requirements
EnglishC1
Spanish(optional)B2
BasicIntermediateAdvancedNative
Why This Job8.5 of 10

This MLOps Engineer role offers a unique opportunity to work with a leading AI start-up focusing on innovative technologies. Enjoy competitive compensation and flexible work arrangements.

Salary Range
Required
0/1
Optional
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Bonus
0/1

About European Tech Recruit

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Industry
Tech
Location
Remote

Who Will Succeed Here

Proficient in MLOps tools and frameworks such as DeepSpeed and FSDP, with hands-on experience in deploying machine learning models in production environments using AWS or Azure.

Self-motivated and disciplined to thrive in a remote work environment, demonstrating strong time management skills to balance multiple projects and meet tight deadlines.

Analytical mindset with a focus on performance optimization, specifically in model compression techniques and deployment strategies to enhance inference efficiency and reduce operational costs.

Learning Resources

MLOps: Machine Learning Operationscourse

Career Path

MLOps Engineer(Now)Senior MLOps Engineer(1-2 years)Lead MLOps Engineer or AI Solutions Architect(3-5 years)

Market Overview

Market Size 2024
$3.5B
Annual Growth
27.4%
AI Adoption
75%
Investment
+150%
Labour Demand
+40%
Avg Salary
$130K

Skills & Requirements

Required
MLOpsDeepSpeedFSDP
Growing in Demand
Machine Learning EngineeringDataOpsCloud Security
Declining
Traditional Data WarehousingManual Model Deployment

Domain Trends

Increased Adoption of MLOps Frameworks
Companies are increasingly adopting frameworks like MLflow and Kubeflow to streamline MLOps processes, with a reported 60% of organizations implementing such frameworks in their workflows.
Shift Towards Automated Machine Learning (AutoML)
The demand for AutoML tools is rising, with a 50% increase in usage reported over the past year, enabling faster model development and deployment.
Integration of MLOps with DevSecOps
There is a growing trend to integrate MLOps practices with DevSecOps to enhance security in AI deployments, with 45% of enterprises planning to adopt this integrated approach by 2025.

Industry News

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