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Mid/Senior Solution Architect

Multiverse Computing
Doha, QAT
Full Time
Mid
Hybrid
3 weeks ago
AWSAzureGCPAI/MLMLOpsDocker
Free

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About Multiverse Computing

  • Multiverse Computing is a fast growing deep tech company founded in 2019, recognized as one of the 100 most promising AI companies globally.
  • We are the largest quantum software company in the EU, with 250+ employees worldwide building advanced AI and quantum solutions.
  • Our mission is to enable organizations to gain a meaningful competitive edge through cutting edge AI and quantum technologies.

Key requirements

  • Previous experience in a technical partner pre sales or consulting role with heavy emphasis on partner and customer facing interactions
  • Excellent communication and presentation skills
  • Strong knowledge of cloud platforms (AWS, Azure, GCP) and AI/ML services
  • Familiarity with MLOps tools and practices
  • Proficiency with Docker and Kubernetes for AI workload containerization
  • Understanding of LLM inference stacks and model delivery formats
  • Experience sizing GPU infrastructure for LLM inference or training workloads
  • Experience benchmarking and evaluating LLM performance
  • Hands on coding skills in Python, SQL, and familiarity with ML libraries and frameworks
  • Bachelor's or master's degree in Computer Science, Data Science, Engineering, or related field
  • Must be available to travel as needed
  • Languages: Arabic and English

Preferred Qualifications

  • Experience with Computer Vision models, Speech models, Vision Language models, and other modalities.
  • Experience with AI model optimization, quantization, or deployment to edge devices.
  • Hands on experience designing RAG pipelines and/or multi agent systems.
  • Experience designing data architectures (batch & streaming) and working with big data technologies.
  • Knowledge of data privacy and ethical considerations in AI, including GDPR compliance.

Perks & Benefits

  • Equal pay guaranteed.
  • Signing bonus.
  • Relocation package (if applicable).
  • Eligibility for educational budget according to internal policy.
  • Hybrid opportunity.
  • Flexible working hours.
  • Language classes and discounted lunch options.
  • Working in a high paced environment, working on cutting edge technologies.
  • Career plan. Opportunity to learn and teach.

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