AI Engineer - R&D to Production (Multi-Modal: Video, Text, Audio)
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Experience: 4–5+ Years
Employment Type: Full-Time
Hiring Partner: Flatgigs
Client: Confidential AI Research & Innovation Lab
About the Opportunity
Flatgigs is hiring AI Engineers for a confidential R&D-focused AI lab working across video, text, and audio problem spaces.
This is not a typical “apply a model and ship” role.
This is a research-driven environment where problems are not clearly defined, and solutions are not obvious.
You will spend time:
• Exploring
• Experimenting
• Failing
• Iterating
• And eventually solving problems that don’t have playbooks If you need structured tasks and predictable outputs — this role will frustrate you.
If you enjoy going deep into problems and figuring things out from first principles — this is where you’ll thrive.
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 / 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 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
•
Why This Role
• Work on open-ended, high-impact AI problems
• Opportunity to explore across multiple AI domains
• Be part of a true R&D environment, not just product delivery
• Freedom to experiment, fail, and learn
Hiring Approach
• This is an ongoing hiring effort, not tied to a fixed headcount
• Quality matters more than speed or volume
• Strong candidates are hired continuously as they are identified
Confidentiality Note
This opportunity is being managed by Flatgigs on behalf of a confidential client. Client details will be shared with shortlisted candidates during the hiring process.
Requirements
- •4–5+ years of experience in AI / Machine Learning
- •Experience across at least two of the following areas: Video, Text (NLP / LLMs), Audio (bonus)
- •Prior experience working in research or experimentation-heavy environments
- •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
- •Curious by nature — asks “why” more than “what”
- •Comfortable working in uncertain, ambiguous problem spaces
Nice to Have
- •Candidates limited to only one vertical may struggle in this environment
- •Publications (nice to have, not mandatory)
- •Enjoys experimentation and is not discouraged by failure
- •Thinks in terms of systems, patterns, and root causes
- •Has a tinkerer mindset — explores beyond surface-level fixes
- •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
Responsibilities
- •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
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