Senior Computer Vision / ML Engineer

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.