
- Early StageStartup in initial stages
Senior Computer Vision / ML Engineer
- ₹10L – ₹18L • 0.1% – 0.2%
- |Gurgaon •
- |3 years of exp
- |Full Time
About the job
About Artikate Studio
We're a deep-tech engineering firm that has been building software since 2016. We engineer AI-powered systems for defence institutions, government bodies, national-scale enterprises, and D2C brands — from a single AI module to entire mission-critical platforms. We're AWS and GCP Certified Partners, Razorpay Technology Partners, and Red Hat Partners.
Our engineers are dedicated, senior-led teams that embed with our clients, ship working software every two weeks, and work to a defence-grade security baseline as standard.
About the role
We're hiring a Senior Computer Vision / ML Engineer to build the AI that powers our systems — real-time detection and inspection across multi feeds, models that run on the edge and in air-gapped environments, and pipelines that keep them accurate in production. This is a hands-on builder role: you'll own models end to end, from data and training through optimization and deployment, working alongside our Solution Architect and platform engineers.
If you've shipped computer-vision models that ran reliably in the real world — not just in a notebook — and you care about latency, robustness, and what happens after the model is "done," this is for you.
What you'll build
- Train, fine-tune and evaluate detection, classification and segmentation models (YOLO-family and similar) for production accuracy and robustness.
- Own data pipelines — collection, annotation workflows and QA, augmentation, and dataset versioning — because model quality starts with data quality.
- Optimize models for edge and on-prem inference — quantization, ONNX / TensorRT, and latency/throughput tuning on GPU and edge devices.
- Build real-time, multi-camera / multi-feed inference systems that hold accuracy at scale.
- Deploy into air-gapped and on-premise environments, and stand up retraining / continuous-learning loops so models improve over time.
- Write clean, tested, maintainable code and collaborate closely on architecture and integration.
Must-have experience
- 3–7 years building production ML / computer-vision systems — models that actually shipped and ran in the field.
- Strong Python and PyTorch (TensorFlow a plus).
- Deep computer vision: object detection, segmentation, and classification (YOLO-family, Detectron, or equivalent), plus OpenCV.
- Model optimization and deployment: ONNX, TensorRT, quantization, and edge/GPU inference.
- Hands-on with data and annotation pipelines — labelling workflows, QA, dataset versioning.
- Solid software-engineering fundamentals: Git, testing, clean code, Docker.
- Comfortable owning a model end to end, from raw data to a deployed, monitored system.
Nice to have
- Edge AI hardware (NVIDIA Jetson) and GPU-cluster experience.
- MLOps tooling — model registry, monitoring, retraining pipelines.
- Air-gapped / on-prem deployment and handling of sensitive or classified data.
- LLM / RAG exposure (Llama-class, LangChain, Hugging Face) and ASR (Whisper).
- Industrial / manufacturing machine vision and harsh-environment deployment; awareness of PLC/CNC integration.
- Cloud (AWS / GCP).
How we work
- Senior-led delivery — no hand-off to juniors after the pitch.
- 2-week sprint velocity — working software every fortnight.
- Defence-grade security baseline — air-gapped and zero-egress are everyday work.
- Embedded partnership — dedicated teams that treat the client's product as their own.
- IST-aligned — no timezone friction.
Engagement details
- Location: Gurugram, with occasional travel to client sites.
- Type: Full-time, senior individual contributor.
- Start: Immediate.
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