AI Project Lead — End-to-End ML & MLOps

LanceSoft, Inc.

United Arab Emirates

On-site

AED 133,000 - 180,000

Full time

2 days ago
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Job summary

LanceSoft, Inc. seeks an AI Project Specialist in Dubai to lead end-to-end AI initiatives from problem framing to deployment and user adoption.

You will coordinate with cross-functional teams and external vendors, leverage Python/SQL, ML fundamentals, and advanced generative AI techniques in a regulated environment where accuracy and governance matter. The role emphasizes data modeling, API integrations with enterprise systems, and robust MLOps practices across cloud platforms.

Qualifications

  • Experience delivering end-to-end solutions from problem definition to deployment.
  • Ability to coordinate cross-functional teams and external vendors.
  • Strong Python and SQL skills with software engineering practices.
  • Solid ML foundation and experience with supervised/unsupervised methods.
  • Hands-on with generative AI, LLMs, prompts, and retrieval augmented generation.
  • Data modeling, pipelines, and enterprise system integrations via APIs.
  • Experience with deployment and MLOps including containerization and CI/CD.
  • Familiarity with cloud AI services and vector databases is a plus.
  • Project management skills with Agile/PMO practices; PMP/PRINCE2 is a plus.

Skills

End-to-end delivery
Stakeholder coordination
Python programming
SQL
Machine learning basics
Generative AI / LLMs
Data modeling & pipelines
MLOps / CI/CD
Cloud platforms
Agile / PMO
Vendor management
Arabic language (adv)

Tools

Git
Docker
APIs

Job description

LanceSoft, Inc. seeks an AI Project Specialist in Dubai to lead end-to-end AI initiatives from problem framing to deployment and user adoption.

You will coordinate with cross-functional teams and external vendors, leverage Python/SQL, ML fundamentals, and advanced generative AI techniques in a regulated environment where accuracy and governance matter. The role emphasizes data modeling, API integrations with enterprise systems, and robust MLOps practices across cloud platforms.

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