You will get a custom API for your machine learning workflow
Top Rated
Top Rated
Project details
Deploy your machine learning models as robust, scalable APIs on the cloud! Our skilled, multi-disciplinary team develops custom APIs tailored to your business logic. Ideal for any scale, from single instances to thousands, our APIs support asynchronous execution with dynamic batching via WebSockets and WebRTC for optimal responsiveness.
Machine Learning Tools
Amazon SageMaker, Azure Machine Learning, ChatGPT, Google AutoML, Google Data Studio, GPT-3, Keras, Kubeflow, MLflow, NumPy, NVIDIA AI Platform, Open Neural Network Exchange, OpenCV, pandas, Python, Python Scikit-Learn, scikit-learn, SciPy, Scrapy, TensorFlow, Tesseract OCR, Vertex AI, Word2vec, XGBoostWhat's included
| Service Tiers |
Starter
$1,000
|
Standard
$3,000
|
Advanced
$15,000
|
|---|---|---|---|
| Delivery Time | 7 days | 20 days | 60 days |
Number of Revisions | 1 | 2 | 3 |
Number of Model Variations | 1 | 2 | 4 |
Number of Scenarios | 1 | 2 | 4 |
Number of Graphs/Charts | 1 | 2 | 4 |
Model Validation/Testing | - | ||
Model Documentation | - | ||
Data Source Connectivity | - | ||
Source Code |
Optional add-ons
You can add these on the next page.
Model Validation/Testing
(+ 3 Days)
+$400
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SH
Shafee H.
May 26, 2025
Senior Frontend Dev
RH
Romeo H.
Jul 21, 2024
3d scan of face to 3d avatar to AR
Helped me with in incredibly difficult task and without him not sure where I would be with my project!
LL
Loïc L.
May 29, 2024
Outfit detection prototype
SH
Shafee H.
Feb 5, 2024
Machine Learning
Excellent developer, very bright.
SH
Shafee H.
Jan 6, 2024
StyleGAN A.I. Expert
Great work
About Muhammad Abdullah
Senior Computer Vision & ML Consultant | Triton | PyTorch | Postgres
100%
Job Success
Rawalpindi, Pakistan - 10:04 am local time
𝐍𝐨𝐭𝐜𝐡𝐚 𝐀𝐯𝐞𝐫𝐚𝐠𝐞 𝐂𝐨𝐦𝐩𝐮𝐭𝐞𝐫 𝐕𝐢𝐬𝐢𝐨𝐧 𝐆𝐮𝐲 😎
I don’t stop at a cool demo. Shipping LootMart (hyper-local marketplace) taught me the full stack around models: clean APIs, rock-solid data contracts, observability, security, and predictable costs. That’s why my CV/ML services behave like products, not science projects.
𝐖𝐡𝐚𝐭 𝐈 𝐀𝐜𝐭𝐮𝐚𝐥𝐥𝐲 𝐃𝐨
- Computer Vision & Video Analytics (2D/3D): detection (YOLO/DETR), multi-object tracking (ByteTrack/DeepSORT), segmentation (U-Net), OCR/document AI, pose/re-ID, visual search & face/product matching (Siamese + Triplet Loss), point clouds & geometry.
- High-Throughput Inference: NVIDIA Triton (dynamic batching, concurrent models, HTTP/gRPC), TensorRT (FP16), ONNX Runtime; autoscaling containers with health checks and graceful rollouts.
- Robust Ingestion: multi-RTSP pipelines with back-pressure control using OpenCV, FFmpeg, PyAV/decord so frames don’t mysteriously vanish under load.
- MLOps & Services: FastAPI/Flask gateways, worker queues, CI/CD, Docker + Nginx; W&B for experiments; versioned datasets; reproducible training.
- Data & Integrations: Postgres (schema design, RLS, SQL/PLpgSQL), Redis, vector DBs (Milvus/Qdrant), webhook-driven architectures, n8n workflows for ETL/alerts, and MCP (Model Context Protocol) to wire AI tools into your internal systems.
- Selective Full-Stack Glue (when it helps): Next.js app layers, secure webhooks, auth, real-time updates, and crisp dashboards so stakeholders can see impact.
𝐏𝐫𝐨𝐨𝐟 𝐢𝐧 𝐭𝐡𝐞 𝐏𝐮𝐝𝐝𝐢𝐧𝐠 (𝐑𝐞𝐜𝐞𝐧𝐭 𝐖𝐢𝐧𝐬)
1. Triton-backed real-time CCTV analytics across multiple cameras on commodity GPUs (dynamic batching = buttery latency).
2. Visual matching pipelines (Siamese/Triplet) for search/dedupe with rigorous evals and W&B tracking.
3. Heavy research models → ONNX/TensorRT → low-latency services that actually survive production traffic.
4. Production plumbing that lasts: Postgres-first data contracts, webhook fan-out, n8n automations... no brittle glue.
𝐇𝐨𝐰 𝐖𝐞’𝐥𝐥 𝐖𝐨𝐫𝐤 (𝐑𝐎𝐈 𝐅𝐢𝐫𝐬𝐭, 𝐀𝐥𝐰𝐚𝐲𝐬)
1. 30-min discovery → lock in the KPI (latency, accuracy, throughput, cost).
2. Roadmap & estimate → phases, risks, acceptance tests.
3. Build & validate → baselines first, then iterate; measurable deltas each milestone.
4. Handoff & scale → docs, runbooks, and knowledge transfer so your team owns it.
𝐂𝐨𝐫𝐞 𝐒𝐭𝐚𝐜𝐤
Python • PyTorch • TensorRT • ONNX Runtime • NVIDIA Triton • OpenCV • Kornia • FFmpeg • PyAV/decord • Postgres • Redis • Milvus/Qdrant • FastAPI/Flask • Next.js • Docker • Nginx • Weights & Biases • Webhooks • n8n • MCP
𝐀𝐯𝐚𝐢𝐥𝐚𝐛𝐢𝐥𝐢𝐭𝐲
Consulting/part-time (fractional) engagements: architecture reviews, performance tuning, prototypes, or owning a CV/ML workstream. Top-rated on Upwork. Minimum $100/hr.
If you want production-ready computer vision, real-time video, reliable pipelines, and clear ROI, 𝐥𝐞𝐭’𝐬 𝐭𝐚𝐥𝐤. I’ll map your goal to a pragmatic plan and ship results you can measure.
Steps for completing your project
After purchasing the project, send requirements so Muhammad Abdullah can start the project.
Delivery time starts when Muhammad Abdullah receives requirements from you.
Muhammad Abdullah works on your project following the steps below.
Revisions may occur after the delivery date.
Define the scope
We discuss the requirements with you and prepare a project proposal (delineating the scope of the project, timeline, deliverables, etc.) and a specification document (optional) to specify the endpoints early on.
Work on the API development (providing you regular status updates)
We usually go with weekly scrums however we are open to your suggestions. We track issues using Linear or Jira which keeps the discussion organized and active. It also helps us incorporate your feedback into the development process.