You will get Custom AI Model Training | Fine-Tuning LLMs, GPT, BERT & ML Models

Amar S.Status: Offline
Amar S. Amar S.
4.9
Top Rated

Let a pro handle the details

Buy Machine Learning services from Amar, priced and ready to go.
Amar S.Status: Offline
Amar S. Amar S.
4.9
Top Rated

Let a pro handle the details

Buy Machine Learning services from Amar, priced and ready to go.

Project details

Need a custom AI model trained on your data that delivers real results?

I train and fine-tune machine learning models from LLMs (GPT, BERT, LLaMA) to computer vision and NLP models tailored to your specific business problem using PyTorch, TensorFlow, and cloud platforms.

What You Get:
→ Custom model training or fine-tuning on your dataset
→ LLM fine-tuning (GPT, BERT, LLaMA) for domain-specific tasks
→ Hyperparameter optimization for peak model performance
→ Data preprocessing, cleaning, labeling & augmentation
→ Detailed evaluation report with accuracy, F1 & performance metrics
→ Production deployment as REST API on AWS, Azure or GCP

Who This Is For:
→ Businesses needing AI models for classification, prediction or NLP tasks
→ Teams wanting to fine-tune LLMs on proprietary company data
→ Startups building AI-powered products that need custom trained models

I don't just train models I build complete ML pipelines from data prep to production deployment. Every model comes with full source code, documentation, and ongoing support.

Share your dataset and project goals I will propose the best model architecture!
Machine Learning Tools
Amazon SageMaker, Apache Spark MLlib, Azure Machine Learning, BERT, ChatGPT, Databricks MLflow, GitHub Copilot, Google AutoML, GPT-3, H2O, Keras, Kubeflow, MLflow, NLTK, NumPy, NVIDIA AI Platform, OpenCV, pandas, Python, Python Scikit-Learn, PyTorch, SciPy, TensorFlow, Vertex AI, XGBoost
What's included
Service Tiers Starter
$250
Standard
$700
Advanced
$2,000
Delivery Time 7 days 14 days 28 days
Number of Revisions
235
Model Validation/Testing
-
Model Documentation
-
Data Source Connectivity
Source Code

Frequently asked questions

4.9
10 reviews
90% Complete
10% Complete
1% Complete
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TM

Tracy M.
5.00
Jul 20, 2026
GenAI Engineer for AI Image and Video Generation Pipeline (ComfyUI, Flux, SDXL, Turbo-Z, LoRA) Exactly what we hoped for. He delivered a complete, production-ready ComfyUI environment with FLUX, SDXL, LoRA support, video workflows, and auto-scaling API endpoints, all documented so clearly that our team was generating images the very same day. He clearly knows this stack inside and out, communicated effectively throughout the project, and delivered everything on time. We'll definitely hire him again in the future.

BJ

Baynton J.
5.00
Dec 14, 2025
AI & Data Engineering Specialist Needed for NLP and Deep Learning Projects Amar did an excellent job. He reviewed and finalized our AI & data engineering system. He quickly understood the existing architecture, fixed NLP and data pipeline issues, and improved overall system stability. Communication was clear, work was well-documented, and everything was delivered on time. We would definitely work with him again for future enhancements.

ME

Mudasar E.
5.00
Dec 2, 2025
Senior Generative AI & Automation Engineer | LLMs, Python, n8n, FastAPIs, Webhooks I rarely write long reviews, but the quality of work I received truly deserves it.
I hired him for a highly complex project involving Generative AI, LLM integrations, and automation workflows, and he exceeded all my expectations. I needed someone to wrap up the project for me, and I’m genuinely glad I found the right person.

KH

Kimberly H.
3.85
Mar 3, 2025
Grafana Expert

MR

Merlo R.
5.00
Dec 3, 2024
get all the estimates whose status is sent through this API call Amar was awesome to work with. He replied to all of our asks and made everything very easy for us
Amar S.Status: Offline

About Amar

Amar S.Status: Offline
Multimodal AI Engineer | GenAI, AI Image/Video Pipelines, ComfyUI/LoRA
100% Job Success
4.9  (10 reviews)
Lahore, Pakistan - 11:35 am local time
I build production-grade Multimodal AI pipelines - systems where LLMs, image generation, video, and audio work together as one reliable product, with evals built in so quality is measured, not guessed. Photo in, personalized story and consistent illustrations out. Not prototypes that impress in a demo, but pipelines that ship, scale, and stay consistent in production.

Most AI projects don't fail at the idea stage - they stall at 80%. The prototype works, then it never becomes a product clients can trust: characters drift between images, outputs break schemas, accuracy is a guess. That last stretch - consistency, structured outputs, evaluation, real deployment - is exactly what I do. 10+ years in software, now focused entirely on Multimodal and Generative AI.

𝐖𝐡𝐚𝐭 𝐈 𝐁𝐮𝐢𝐥𝐝:

- Multimodal AI pipelines: end-to-end systems combining LLM story/content generation (structured JSON schemas) with image generation - identity-locked characters across hundreds of pages, outfit consistency, emotion and expression control, multi-character scenes, reference-image workflows.

- AI image generation pipelines: ComfyUI, Flux / FLUX.2, SDXL, Nano Banana - with LoRA training (Kohya, ai-toolkit), ControlNet, IPAdapter, PuLID/InstantID face locking, inpainting, and Runware/API-based generation for production consistency and quality control.

- AI video generation pipelines: image-to-video and text-to-video using WAN 2.2, LTX, Kling, Veo, Runway, Seedance - plus audio-driven lip-sync, talking avatars, and motion-controlled animation systems.

- AI UGC and ad creatives: scroll-stopping product showcase videos, UGC-style ads, and short-form marketing content for TikTok, Reels, and Meta campaigns - built as repeatable AI pipelines, not one-off edits.

- Audio & speech: Whisper speech-to-text, ElevenLabs TTS and voice cloning, photo & audio to talking-avatar video pipelines.

- LLM & VLM integration: GPT-4o/5-class vision, Claude, Gemini integrated into business systems - structured outputs, schema validation, RAG with LangChain/LangGraph and vector DBs (Pinecone, FAISS).

- LLM/VLM Evals & quality optimization: golden datasets, LLM-as-judge and VLM-as-judge scoring, experiment-driven prompt optimization, regression testing with Langfuse/Promptfoo/Braintrust - so accuracy becomes a tracked number ("71% to 84% in three cycles"), not an opinion.

- AI agents & automation: multi-step agents with CrewAI, AutoGen, MCP integrations, and n8n workflows with LLM-powered decision-making.

- Full-stack developments: React/Next.js frontends, Node.js/FastAPI backends, PostgreSQL - so your AI product ships as one system, not disconnected pieces.

- Deployment: FastAPI backends, Docker, CI/CD for ML pipelines, GPU queue serialization, cost-efficient serverless inference on RunPod/Modal.

𝐑𝐞𝐜𝐞𝐧𝐭 𝐖𝐨𝐫𝐤:

✔️ 𝗣𝗲𝗿𝘀𝗼𝗻𝗮𝗹𝗶𝘇𝗲𝗱 𝗔𝗜 𝗦𝘁𝗼𝗿𝘆𝗯𝗼𝗼𝗸 𝗣𝗹𝗮𝘁𝗳𝗼𝗿𝗺: children's book illustration pipeline - hero photo & child's details in; stylized character reference, structured 15-page story JSON, and identity-consistent page illustrations out (Flux & Runware). Personalized storybooks with character, outfit, and expression consistency at production scale.

✔️ 𝗗𝗔𝗧𝗔𝗦𝗜𝗠: AI character generation platform with dual ComfyUI pipelines, automated LoRA training, quality gating, and GPU queue serialization - thousands of identity-locked images.

✔️ 𝗩𝗟𝗠 𝗔𝗰𝗰𝘂𝗿𝗮𝗰𝘆 𝗢𝗽𝘁𝗶𝗺𝗶𝘇𝗮𝘁𝗶𝗼𝗻: eval pipeline for a food-photo-to-calories feature - golden dataset, automated scoring, experiment-driven prompt iteration to lift real accuracy.

✔️ 𝗝𝗼𝘆𝗣𝗶𝘅: AI talking-video platform - photo & audio in, lip-synced avatar video out, identity preserved at scale.

✔️ 𝗛𝗶𝗿𝗲𝗛𝗮𝗿𝗿𝘆: multi-agent AI platform backend - LLM task automation with production-safe structured outputs and deterministic state transitions.

You'll get daily updates, clear milestones, and a fully documented handover - so your team can run the system without me. If your project involves multimodal AI, image or video generation pipelines, LLM/VLM integration, evals, or getting any of it actually deployed and reliable - send me the details and I'll tell you exactly how I'd build it.

𝐓𝐞𝐜𝐡: ComfyUI, Flux, FLUX.2, SDXL, Nano Banana, Stable Diffusion, LoRA, Kohya, ai-toolkit, ControlNet, IPAdapter, PuLID, InstantID, Runware, WAN 2.2, LTX, Kling, Veo, Runway, Seedance, HeyGen, Wav2Lip, Whisper, ElevenLabs, TTS, FFmpeg, PyTorch, OpenCV, GPT-4o, Claude, Gemini, Llama, LangChain, LangGraph, RAG, Pinecone, FAISS, CrewAI, AutoGen, MCP, n8n, Langfuse, Promptfoo, FastAPI, Python, Node.js, React, Next.js, PostgreSQL, Docker, RunPod, Modal, AWS.

Note: I don't take on NSFW, adult, or explicit content projects.

Steps for completing your project

After purchasing the project, send requirements so Amar can start the project.

Delivery time starts when Amar receives requirements from you.

Amar works on your project following the steps below.

Revisions may occur after the delivery date.

Data Review & Problem Scoping

I'll analyze your dataset, define model objectives, select the right architecture, and create a detailed training plan with expected performance metrics.

Data Preprocessing & Preparation

I'll clean, label, augment, and split your data into training, validation, and test sets. Handle missing values, class imbalance, and feature engineering.

Review the work, release payment, and leave feedback to Amar.