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Lead MLOps Engineer

3 weeks ago
Bangladesh
Full-time
Lead
Machine Learning Engineer
Software Development
CI/CD Docker Generative AI Kubernetes LLM MLOps Python
Apply Now
NexGen Cloud

NexGen Cloud

NexGen Cloud is Europe's leading sustainable cloud Infrastructure as a Service (IaaS) provider, specializing in high-performance computing (HPC) and GPU infrastructure. With a focus on sustainability and innovation, NexGen Cloud offers GPU as a Service...

IT Services
11-50
Founded 2020
View All Jobs 8

Description

  • Own the design, implementation, and evolution of core MLOps systems across Hyperstack, including the infrastructure and workflows behind AI Studio.
  • Build and improve orchestration systems for model training, fine-tuning, evaluation, and deployment for large GPU workloads.
  • Own production readiness for ML infrastructure, including monitoring, alerting, incident response, and continuous improvement.
  • Define and embed MLOps practices such as model versioning, reproducibility, deployment safety, rollback strategies, and environment management.
  • Provide technical leadership through architecture decisions, implementation guidance, and shared engineering standards.
  • Work closely with Product, Engineering, and cross-functional teams to shape the platform and its operating model.
  • Support reliable and repeatable production ML operations for complex, asynchronous, resource-intensive workloads.

Requirements

  • Proven experience designing, building, and operating production ML infrastructure, platform systems, or MLOps workflows in cloud environments.
  • Hands-on Python development experience, including backend systems, automation, and developer or platform tooling.
  • Experience supporting LLM, generative AI, or fine-tuning workflows in production, including training, evaluation, deployment, inference, and lifecycle management.
  • Production-grade experience with Docker, Kubernetes, CI/CD, and infrastructure-as-code in operational environments.
  • Experience owning complex, asynchronous, or resource-intensive workloads end to end, including orchestration, reliability, observability, and incident response.
  • Ability to work cross-functionally and provide technical leadership through influence across engineering teams.
  • Exposure to GPU-intensive, distributed, or performance-sensitive ML workloads is preferred.
  • Experience building internal developer platforms or tooling that improve experimentation, reproducibility, and delivery speed for ML teams is preferred.
  • Background in cloud infrastructure, platform products, or technically complex B2B software is preferred.

Benefits

  • Competitive salary and annual discretionary bonus scheme.
  • Employee wellbeing benefits.
  • 25 days of holiday plus public holidays.
  • Flexible working arrangements, including remote or hybrid options depending on role and location.
  • Real ownership and autonomy with the trust to take initiative and experiment.
  • Opportunity to make a visible, meaningful impact as the company scales.
  • Clear career progression and growth opportunities in a fast-growing company.
  • A collaborative, international culture built on trust, transparency, and ownership.

Interested in this position?

Apply directly on the company website

Apply Now

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