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IT Engineer

  • On-site
    • Stockholm, Stockholms län, Sweden
    • Bromolla, Skåne län, Sweden
    +1 more
  • Engineering

Job description

At TechBiz Global, we are providing recruitment service to our TOP clients from our portfolio.
We are currently looking for a highly proactive and detail-oriented IT Engineer to join one of our clients' teams. If you're looking for an exciting opportunity to grow in an innovative environment, this could be the perfect fit for you.


Key Responsibilities:

  • Infrastructure: Designing/implementing/maintaining scalable server clusters optimized for GPU performance to support demanding workloads.

  • Cloud Platforms: Utilizng cloud platforms that provide enhanced GPU capabilities, ensuring optimal resource utilization.

  • Performance Optimization : Implementing strategies to ensure efficient allocation of CPU, GPU, and memory resources to maximize application performance.

  • Security Configuration: Establishing robust security measures tailored to GPU and cloud environments, including access controls and encryption.

  • Backup and Recovery: Designing and managing backup strategies to ensure data protection in the GPUaaS platform, with recovery mechanisms for quick restores

  • Performance Monitoring: Continuously monitoring system performance to identify bottlenecks and enhance scalability and efficiency

  • Collaboration: Working closely with service management and support team, architects, and stakeholders to design new features or services that leverage GPU acceleration.

Job requirements

  • Relevant degree in Computer Science, Information Technology, or a related field from an accredited institution.

  • Extensive expertise in cloud platforms and GPU optimization techniques, with a deep understanding of GPU-accelerated workloads.

  • At least 3-5 years of experience as an IT Engineer, ideally within a cloud-first environment.

  • Experience with GPU and AI/ML accelerators is highly beneficial.

  • Certifications like CompTIA Linux+ can be considered as an additional bonus.

  • Experience with Kubernetes and container orchestration for managing GPU clusters.

  • Familiarity with machine learning frameworks that utilize GPUs (e.g., TensorFlow, PyTorch).

  • Knowledge of GPU hardware specifications and optimization techniques for performance enhancement.

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