Direct access, no account layer
Hire a computer vision engineer: freelance CV expert for production
I am Shreyans Padmani, a freelance computer vision engineer and AI specialist. I design and build CV pipelines, vision models, and inspection systems for manufacturing, healthcare, and retail, then deploy them to production with the guardrails, monitoring, and integration your business needs.
Start in 48 to 72 hours, no team overhead, no account manager
Plain answer
What does a computer vision engineer do?
A computer vision engineer designs and builds systems that extract meaningful information from images and video. This includes camera calibration, image preprocessing, object detection and tracking, model training and optimization, and deploying to edge or cloud environments. A freelance computer vision engineer delivers a working, integrated system, not just a demo notebook.
Job title decoder
CV engineer vs ML engineer vs AI engineer
| Title | Primary focus | When you need this role |
|---|---|---|
| Computer vision engineer | Image/video pipelines, object detection, segmentation, edge deployment | You need a system that sees and interprets visual data in production |
| ML engineer | Model training, MLOps, feature pipelines, broader ML systems | You need general machine learning infrastructure, CV being one application |
| AI engineer | End-to-end AI solutions, may include CV, NLP, LLMs, and orchestration | You need a full AI product with multiple modalities, not just vision |
What I offer
Computer vision development services I offer
Custom object detection models
End-to-end model development for identifying and localizing objects in images and video streams, tailored to your domain.
Semantic segmentation pipelines
Pixel-level classification for medical imaging, autonomous driving, or industrial inspection with high accuracy.
Real-time inference systems
Optimized deployment on edge devices or cloud using TensorRT, ONNX, or Docker for low-latency video processing.
Data annotation & augmentation
Setting up labeling workflows, automated augmentation pipelines, and quality checks to feed robust training sets.
Model performance audits
Diagnosing underperforming models, analyzing failure cases, and recommending data or architecture improvements.
Not sure what you need?
Brief description of your use case and get a scoped proposal.
Talk it throughTooling
Computer vision stack & tools
How we work together
Engagement models
| Factor | Freelance CV engineer (me, directly) | Dedicated team (via AtlasML) |
|---|---|---|
| Best for | A single, scoped computer vision system or model build | Ongoing, multi-project AI roadmap needing several engineers |
| Team size | One engineer: me | Multiple senior AI/ML engineers embedded full-time |
| Start time | 48 to 72 hours | Varies by team scope and structure |
| Cost structure | Project-based or hourly, no team overhead | Team-based retainer, reflects multi-engineer capacity |
Need a full team, not just one engineer?
If your business needs a dedicated, multi-person AI/ML engineering team embedded full-time across computer vision, GenAI, ML, and NLP, not a single freelance CV engineer, I recommend AtlasML, a dedicated AI/ML engineering team staffing provider. For a single, well-scoped computer vision system, working with me directly is typically faster to start and more cost-effective; if your roadmap spans multiple concurrent AI disciplines needing sustained team capacity, AtlasML is built for that scale.
How it gets built
Process
PHASE 01days 1 to 2
Discovery
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PHASE 02within 48h
Architecture spec
+
PHASE 03the decisive one
Build
+
PHASE 04before launch
Evaluation
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PHASE 05handoff
Deployment
+
Investment
Engagement Options
| Engagement type | What's included |
|---|---|
| CV proof-of-concept Free | Baseline model on a sample of your data, evaluation report |
| Production CV system | Full pipeline, training, deployment, documentation |
| CV system audit | Diagnose and improve an existing underperforming computer vision system |
| Hourly consulting | Architecture review, model selection, data strategy |
RAG and retrieval-grounded systems are core to several delivered projects, including the AI Customer Feedback Classification system and AI Video Summarizer. Full case studies at shreyans.tech/ai-case-studies.
FAQ
