Turn newly trained research models into functional playgrounds, APIs and proofs-of-concept so they can be rapidly validated, demonstrated and handed to the production engineering team.
The outcomes you will own
Model-to-app prototypes
Gradio/Streamlit playgrounds
FastAPI/Flask wrappers
inference integration
edge-case validation
API contracts
structured handover repositories.
What you will do
Translate model weights and checkpoints into interactive prototypes
build backend inference endpoints and schemas
handle text/audio/video inputs and streaming responses
stress-test model behavior
document limits
package functional repositories
hand over API contracts and function blocks to production engineering
maintain high-velocity sync with the Dubai R&D; pod.
What you must bring
1–5 years in ML prototyping or Python application engineering
advanced Python including async/await
Gradio
Streamlit
FastAPI
Flask
Pydantic
PyTorch
What will differentiate you
Execution-focused
quick
experimental
technically rigorous
comfortable with crude prototypes
able to work across research and engineering boundaries.
Key deliverables
Speed from model output to working prototype
functional robustness across edge cases
quality of API contracts
clean handover to production
sprint communication and documentation quality.
Why Crucifer Crucifer AI is building an AI-first learning and technology ecosystem from the ground up. You will work in a high-ownership setting where ideas are expected to become working outcomes quickly, with direct access to senior leadership and the chance to shape systems before they become fixed.
📌 Ml Prototype & Application Engineer – Research Pipelines Kolkata (India)
🏢 CRUCIFER AI TECHNOLOGIES
📍 India
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