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naukri

AI Engineer - R&D to Production

Flatgigs
United Arab Emirates, UAE
Senior
3 months ago
Machine LearningDeep LearningPythonTensorFlowPyTorchData Science
Free

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Machine LearningDeep LearningPython
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What You Ll Work On

  • Solve complex AI problems across:
  • Video understanding and processing
  • Text-based AI / NLP systems
  • Audio processing (nice to have, not mandatory)
  • Design, experiment, and iterate on
  • AI models and approaches
  • Work on problems that may not have
  • clear starting points or predefined solutions
  • Explore
  • multiple approaches before arriving at optimal solutions
  • Contribute to
  • research-driven experimentation and innovation

What We Re Looking For Core Requirement

  • 4 5+ years of experience in AI / Machine Learning
  • This level of experience matters because it typically brings exposure to
  • multiple AI domains
  • , not just one.

Multi-Modal Exposure (Important)

  • Experience across
  • at least two of the following areas
  • :
  • Video

• Text (NLP And LLMs)

  • Audio (bonus)
  • Candidates limited to only one vertical may struggle in this environment.

R&D Experience (Critical)

  • Prior experience working in
  • research or experimentation-heavy environments
  • Exposure to:
  • Prototyping
  • Testing hypotheses
  • Iterative experimentation
  • Experience contributing to:
  • Research initiatives
  • Internal innovation projects
  • Publications (nice to have, not mandatory)

Problem-Solving Depth

  • Ability to go beyond making things work and instead:
  • Understand
  • why something works or fails
  • Debug deeply at the
  • model or system level
  • Explore multiple approaches before finalizing a solution

Ideal Candidate Profile

  • Curious by nature asks why more than what
  • Comfortable working in
  • uncertain, ambiguous problem spaces
  • Enjoys experimentation and is not discouraged by failure
  • Thinks in terms of
  • systems, patterns, and root causes
  • Has a strong
  • tinkerer mindset
  • explores beyond surface-level fixes

What Success Looks Like

  • You are able to
  • approach open-ended problems without predefined solutions
  • You explore multiple directions instead of settling for the first working solution
  • You contribute to building
  • deep understanding, not just outputs
  • You can work across
  • different AI problem types without becoming a bottleneck
  • Nice to Have
  • Research papers, publications, or contributions to open-source AI projects
  • Experience with:
  • Multi-modal models
  • LLMs and advanced NLP
  • Computer vision systems
  • Audio processing systems

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