AI Engineer - R&D to Production
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Key skills for this role
About the Role
Solve complex AI problems in video, text, and audio processing; design AI models; require multi-modal exposure and research experience.
Key Skills for This Role
Full Job Posting
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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