I will integrate ai models and llms into your app and deploy them on GPU


About this gig
Got an AI feature that works in a demo but breaks in production? I build and ship AI integrations that hold up under real users.
For the last 5 years, I've worked as an AI engineer building production pipelines for gaming and real-time 3D: LLMs, video matting, camera tracking, animation and material-map models, deployed on cloud GPUs and wired into live web apps.
What I can do for you:
- Integrate OpenAI, Claude, Gemini or open-source models into your app
- Deploy custom or Hugging Face models on Replicate, AWS or your own GPU server
- Build generative AI pipelines for image, video and 3D
- Fine-tune existing models on your data
- Connect it all to your Next.js, React or Python backend
- Reduce GPU cost and latency
Why me:
I don't just call an API. I've trained, optimised, and maintained models in production and handled both frontend and backend integration.
You get clean source code, a working endpoint, documentation and a handover call.
Message me before ordering with your use case and stack so I can recommend the right package.
Get to know Jawad A
Full Stack Blockchain and Gen AI developer
- FromPakistan
- Member sinceNov 2020
- Avg. response time1 hour
- Last delivery1 year
Languages
Urdu, English, Spanish, French
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Other AI Development Services I Offer
FAQ
Which AI models can you integrate?
Hosted APIs such as OpenAI, Claude and Gemini. Hosted platforms such as Replicate and Hugging Face. Also open-source or custom PyTorch models, including image, video, LLM and computer vision models.
Do I need my own GPU or cloud account?
No. I can deploy to Replicate or AWS under your account, so you own the infrastructure and billing. If you already have a GPU server, I can deploy there.
Can you work with my existing codebase?
Yes. I regularly integrate into existing Next.js, React and Python backends, and I adapt to your structure rather than rewriting it.
Will I own the code?
Yes. You receive full source code, deployment configs and documentation.
How do you keep GPU costs down?
I choose the right GPU tier and use queuing, autoscaling and cold-start tuning. Where quality allows, I also optimize or quantize the model.
Can you fine-tune a model for my use case?
Yes, if you have suitable data. I'll assess your dataset first and tell you honestly whether fine-tuning or a better prompt or pipeline is the smarter choice.
